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Klaus-Robert Müller
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- affiliation: Technical University of Berlin, Germany
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2020 – today
- 2024
- [j192]Lorenz Linhardt
, Klaus-Robert Müller
Preemptively pruning Clever-Hans strategies in deep neural networks. Inf. Fusion 103: 102094 (2024) - [j191]Sören Becker, Johanna Vielhaben, Marcel Ackermann, Klaus-Robert Müller
AudioMNIST: Exploring Explainable Artificial Intelligence for audio analysis on a simple benchmark. J. Frankl. Inst. 361(1): 418-428 (2024) - [j190]Khaled Kahouli
Molecular relaxation by reverse diffusion with time step prediction. Mach. Learn. Sci. Technol. 5(3): 35038 (2024) - [j189]Ann-Kathrin Dombrowski
Diffeomorphic Counterfactuals With Generative Models. IEEE Trans. Pattern Anal. Mach. Intell. 46(5): 3257-3274 (2024) - [j188]Pattarawat Chormai
Disentangled Explanations of Neural Network Predictions by Finding Relevant Subspaces. IEEE Trans. Pattern Anal. Mach. Intell. 46(11): 7283-7299 (2024) - [j187]Ali Hashemi
Joint Learning of Full-Structure Noise in Hierarchical Bayesian Regression Models. IEEE Trans. Medical Imaging 43(2): 610-624 (2024) - [j186]Jacob R. Kauffmann
From Clustering to Cluster Explanations via Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 35(2): 1926-1940 (2024) - [c189]Klaus-Robert Müller:
Deep Learning made transferable: studying Brain decoding. BCI 2024: 1-2 - [c188]Lukas Muttenthaler, Robert A. Vandermeulen, Qiuyi Zhang, Thomas Unterthiner, Klaus-Robert Müller:
Set Learning for Accurate and Calibrated Models. ICLR 2024 - [d3]Oliver Eberle
Code and Data for Historical Insights from Sacrobosco Tables Project. Version 1. Zenodo, 2024 [all versions] - [d2]Oliver Eberle
Code and Data for "Historical Insights from Sacrobosco Tables" Project. Version 2. Zenodo, 2024 [all versions] - [d1]Khaled Kahouli
MoreRed: Molecular Relaxation by Reverse Diffusion with Time Step Prediction. Zenodo, 2024 - [i137]Jonas Dippel, Barbara Feulner, Tobias Winterhoff, Simon Schallenberg, Gabriel Dernbach, Andreas Kunft, Stephan Tietz, Philipp Jurmeister, David Horst, Lukas Ruff, Klaus-Robert Müller, Frederick Klauschen, Maximilian Alber:
RudolfV: A Foundation Model by Pathologists for Pathologists. CoRR abs/2401.04079 (2024) - [i136]Dilyara Bareeva, Marina M.-C. Höhne, Alexander Warnecke, Lukas Pirch, Klaus-Robert Müller, Konrad Rieck, Kirill Bykov:
Manipulating Feature Visualizations with Gradient Slingshots. CoRR abs/2401.06122 (2024) - [i135]Simon Letzgus, Klaus-Robert Müller, Grégoire Montavon:
XpertAI: uncovering model strategies for sub-manifolds. CoRR abs/2403.07486 (2024) - [i134]Khaled Kahouli, Stefaan Simon Pierre Hessmann, Klaus-Robert Müller, Shinichi Nakajima, Stefan Gugler, Niklas W. A. Gebauer:
Molecular relaxation by reverse diffusion with time step prediction. CoRR abs/2404.10935 (2024) - [i133]Julius Hense, Mina Jamshidi Idaji, Oliver Eberle, Thomas Schnake, Jonas Dippel, Laure Ciernik, Oliver Buchstab, Andreas Mock, Frederick Klauschen, Klaus-Robert Müller:
xMIL: Insightful Explanations for Multiple Instance Learning in Histopathology. CoRR abs/2406.04280 (2024) - [i132]Kim A. Nicoli, Christopher J. Anders, Lena Funcke, Tobias Hartung, Karl Jansen, Stefan Kühn, Klaus-Robert Müller, Paolo Stornati, Pan Kessel, Shinichi Nakajima:
Physics-Informed Bayesian Optimization of Variational Quantum Circuits. CoRR abs/2406.06150 (2024) - [i131]Farnoush Rezaei Jafari, Grégoire Montavon, Klaus-Robert Müller, Oliver Eberle:
MambaLRP: Explaining Selective State Space Sequence Models. CoRR abs/2406.07592 (2024) - [i130]Jonas Dippel, Niklas Prenißl, Julius Hense, Philipp Liznerski, Tobias Winterhoff, Simon Schallenberg, Marius Kloft, Oliver Buchstab, David Horst, Maximilian Alber, Lukas Ruff, Klaus-Robert Müller, Frederick Klauschen:
AI-based Anomaly Detection for Clinical-Grade Histopathological Diagnostics. CoRR abs/2406.14866 (2024) - [i129]Parastoo Semnani, Mihail Bogojeski, Florian Bley, Zizheng Zhang, Qiong Wu, Thomas Kneib, Jan Herrmann, Christoph Weisser, Florina Patcas, Klaus-Robert Müller:
A Machine Learning and Explainable AI Framework Tailored for Unbalanced Experimental Catalyst Discovery. CoRR abs/2407.18935 (2024) - [i128]Jacob R. Kauffmann, Jonas Dippel, Lukas Ruff, Wojciech Samek, Klaus-Robert Müller, Grégoire Montavon:
The Clever Hans Effect in Unsupervised Learning. CoRR abs/2408.08041 (2024) - [i127]Thomas Schnake, Farnoush Rezaei Jafari, Jonas Lederer, Ping Xiong, Shinichi Nakajima, Stefan Gugler, Grégoire Montavon, Klaus-Robert Müller:
Towards Symbolic XAI - Explanation Through Human Understandable Logical Relationships Between Features. CoRR abs/2408.17198 (2024) - [i126]Hartmut Maennel, Oliver T. Unke, Klaus-Robert Müller:
Complete and Efficient Covariants for 3D Point Configurations with Application to Learning Molecular Quantum Properties. CoRR abs/2409.02730 (2024) - [i125]Lukas Muttenthaler, Klaus Greff, Frieda Born, Bernhard Spitzer, Simon Kornblith, Michael C. Mozer, Klaus-Robert Müller, Thomas Unterthiner, Andrew K. Lampinen:
Aligning Machine and Human Visual Representations across Abstraction Levels. CoRR abs/2409.06509 (2024) - [i124]Marco Morik, Ali Hashemi, Klaus-Robert Müller, Stefan Haufe, Shinichi Nakajima:
Enhancing Brain Source Reconstruction through Physics-Informed 3D Neural Networks. CoRR abs/2411.00143 (2024) - [i123]Marvin Sextro, Gabriel Dernbach, Kai Standvoss, Simon Schallenberg, Frederick Klauschen, Klaus-Robert Müller, Maximilian Alber, Lukas Ruff:
xCG: Explainable Cell Graphs for Survival Prediction in Non-Small Cell Lung Cancer. CoRR abs/2411.07643 (2024) - 2023
- [j185]Armin W. Thomas
Evaluating deep transfer learning for whole-brain cognitive decoding. J. Frankl. Inst. 360(13): 9754-9787 (2023) - [j184]Carmen Vidaurre
Novel multivariate methods to track frequency shifts of neural oscillations in EEG/MEG recordings. NeuroImage 276: 120178 (2023) - [j183]Léo Andéol, Yusei Kawakami, Yuichiro Wada, Takafumi Kanamori
Learning domain invariant representations by joint Wasserstein distance minimization. Neural Networks 167: 233-243 (2023) - [j182]Kai J. Miller
Canonical Response Parameterization: Quantifying the structure of responses to single-pulse intracranial electrical brain stimulation. PLoS Comput. Biol. 19(5) (2023) - [j181]Kirill Bykov, Mayukh Deb, Dennis Grinwald, Klaus-Robert Müller, Marina M.-C. Höhne:
DORA: Exploring Outlier Representations in Deep Neural Networks. Trans. Mach. Learn. Res. 2023 (2023) - [j180]Danny Panknin, Stefan Chmiela, Klaus-Robert Müller, Shinichi Nakajima:
Local Function Complexity for Active Learning via Mixture of Gaussian Processes. Trans. Mach. Learn. Res. 2023 (2023) - [j179]Vignesh Srinivasan
Langevin Cooling for Unsupervised Domain Translation. IEEE Trans. Neural Networks Learn. Syst. 34(10): 7675-7688 (2023) - [c187]Klaus-Robert Müller, Simon M. Hofmann:
Interpreting Deep Learning Models for Multi-modal Neuroimaging. BCI 2023: 1-4 - [c186]Alexander Binder, Leander Weber, Sebastian Lapuschkin
Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations. CVPR 2023: 16143-16152 - [c185]Kirill Bykov
Mark My Words: Dangers of Watermarked Images in ImageNet. ECAI Workshops (1) 2023: 426-434 - [c184]Ping Xiong, Thomas Schnake, Michael Gastegger, Grégoire Montavon, Klaus-Robert Müller, Shinichi Nakajima:
Relevant Walk Search for Explaining Graph Neural Networks. ICML 2023: 38301-38324 - [c183]Kim Nicoli, Christopher J. Anders, Lena Funcke, Tobias Hartung, Karl Jansen, Stefan Kühn, Klaus-Robert Müller, Paolo Stornati, Pan Kessel, Shinichi Nakajima:
Physics-Informed Bayesian Optimization of Variational Quantum Circuits. NeurIPS 2023 - [i122]Kirill Bykov, Klaus-Robert Müller, Marina M.-C. Höhne:
Mark My Words: Dangers of Watermarked Images in ImageNet. CoRR abs/2303.05498 (2023) - [i121]Lorenz Linhardt, Klaus-Robert Müller, Grégoire Montavon:
Preemptively Pruning Clever-Hans Strategies in Deep Neural Networks. CoRR abs/2304.05727 (2023) - [i120]Simon Letzgus, Klaus-Robert Müller:
Towards transparent and robust data-driven wind turbine power curve models. CoRR abs/2304.09835 (2023) - [i119]Lukas Muttenthaler, Robert A. Vandermeulen, Qiuyi Zhang, Thomas Unterthiner
Set Learning for Accurate and Calibrated Models. CoRR abs/2307.02245 (2023) - [i118]J. Thorben Frank, Oliver T. Unke, Klaus-Robert Müller, Stefan Chmiela:
From Peptides to Nanostructures: A Euclidean Transformer for Fast and Stable Machine Learned Force Fields. CoRR abs/2309.15126 (2023) - [i117]Oliver Eberle, Jochen Büttner
Insightful analysis of historical sources at scales beyond human capabilities using unsupervised Machine Learning and XAI. CoRR abs/2310.09091 (2023) - [i116]Ilia Sucholutsky, Lukas Muttenthaler, Adrian Weller, Andi Peng, Andreea Bobu, Been Kim, Bradley C. Love, Erin Grant, Jascha Achterberg, Joshua B. Tenenbaum, Katherine M. Collins, Katherine L. Hermann, Kerem Oktar, Klaus Greff, Martin N. Hebart
Getting aligned on representational alignment. CoRR abs/2310.13018 (2023) - 2022
- [j178]Hassan El-Hajj
An Ever-Expanding Humanities Knowledge Graph: The Sphaera Corpus at the Intersection of Humanities, Data Management, and Machine Learning. Datenbank-Spektrum 22(2): 153-162 (2022) - [j177]Christopher J. Anders
Finding and removing Clever Hans: Using explanation methods to debug and improve deep models. Inf. Fusion 77: 261-295 (2022) - [j176]Rick Wilming
Scrutinizing XAI using linear ground-truth data with suppressor variables. Mach. Learn. 111(5): 1903-1923 (2022) - [j175]Ludwig Winkler
High-fidelity molecular dynamics trajectory reconstruction with bi-directional neural networks. Mach. Learn. Sci. Technol. 3(2): 25011 (2022) - [j174]Mina Jamshidi Idaji
Harmoni: A method for eliminating spurious interactions due to the harmonic components in neuronal data. NeuroImage 252: 119053 (2022) - [j173]Simon M. Hofmann
Towards the interpretability of deep learning models for multi-modal neuroimaging: Finding structural changes of the ageing brain. NeuroImage 261: 119504 (2022) - [j172]Oliver Eberle, Jochen Büttner
Building and Interpreting Deep Similarity Models. IEEE Trans. Pattern Anal. Mach. Intell. 44(3): 1149-1161 (2022) - [j171]Thomas Schnake, Oliver Eberle, Jonas Lederer
Higher-Order Explanations of Graph Neural Networks via Relevant Walks. IEEE Trans. Pattern Anal. Mach. Intell. 44(11): 7581-7596 (2022) - [j170]Ann-Kathrin Dombrowski, Christopher J. Anders
Towards robust explanations for deep neural networks. Pattern Recognit. 121: 108194 (2022) - [j169]Tülay Adali, Rodrigo Capobianco Guido, Tin Kam Ho, Klaus-Robert Müller
Interpretability, Reproducibility, and Replicability [From the Guest Editors]. IEEE Signal Process. Mag. 39(4): 5-7 (2022) - [j168]Simon Letzgus, Patrick Wagner, Jonas Lederer
Toward Explainable Artificial Intelligence for Regression Models: A methodological perspective. IEEE Signal Process. Mag. 39(4): 40-58 (2022) - [j167]Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Klaus-Robert Müller, Marius Kloft:
Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images. Trans. Mach. Learn. Res. 2022 (2022) - [c182]Seong-Whan Lee, Klaus-Robert Müller:
Welcome Message from the General Chairs. BCI 2022: 1- - [c181]Klaus-Robert Müller
Deep Learning for Whole-Brain Cognitive Decoding. BCI 2022: 1-3 - [c180]Ameen Ali, Thomas Schnake, Oliver Eberle, Grégoire Montavon, Klaus-Robert Müller, Lior Wolf:
XAI for Transformers: Better Explanations through Conservative Propagation. ICML 2022: 435-451 - [c179]Ping Xiong, Thomas Schnake, Grégoire Montavon, Klaus-Robert Müller, Shinichi Nakajima:
Efficient Computation of Higher-Order Subgraph Attribution via Message Passing. ICML 2022: 24478-24495 - [c178]J. Thorben Frank, Oliver T. Unke, Klaus-Robert Müller:
So3krates: Equivariant attention for interactions on arbitrary length-scales in molecular systems. NeurIPS 2022 - [e6]Andreas Holzinger
xxAI - Beyond Explainable AI - International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers. Lecture Notes in Computer Science 13200, Springer 2022, ISBN 978-3-031-04082-5 [contents] - [i115]Ludwig Winkler, Klaus-Robert Müller, Huziel E. Sauceda:
Super-resolution in Molecular Dynamics Trajectory Reconstruction with Bi-Directional Neural Networks. CoRR abs/2201.01195 (2022) - [i114]Ann-Kathrin Dombrowski, Klaus-Robert Müller, Wolf-Christian Müller:
Automated Dissipation Control for Turbulence Simulation with Shell Models. CoRR abs/2201.02485 (2022) - [i113]Ameen Ali, Thomas Schnake, Oliver Eberle, Grégoire Montavon, Klaus-Robert Müller, Lior Wolf:
XAI for Transformers: Better Explanations through Conservative Propagation. CoRR abs/2202.07304 (2022) - [i112]Jonas Lederer, Michael Gastegger, Kristof T. Schütt, Michael Kampffmeyer, Klaus-Robert Müller, Oliver T. Unke:
Automatic Identification of Chemical Moieties. CoRR abs/2203.16205 (2022) - [i111]Oliver T. Unke, Martin Stöhr, Stefan Ganscha, Thomas Unterthiner
Accurate Machine Learned Quantum-Mechanical Force Fields for Biomolecular Simulations. CoRR abs/2205.08306 (2022) - [i110]Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Klaus-Robert Müller, Marius Kloft:
Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images. CoRR abs/2205.11474 (2022) - [i109]J. Thorben Frank, Oliver T. Unke, Klaus-Robert Müller:
So3krates - Self-attention for higher-order geometric interactions on arbitrary length-scales. CoRR abs/2205.14276 (2022) - [i108]Kirill Bykov, Mayukh Deb, Dennis Grinwald, Klaus-Robert Müller, Marina M.-C. Höhne:
DORA: Exploring outlier representations in Deep Neural Networks. CoRR abs/2206.04530 (2022) - [i107]Ann-Kathrin Dombrowski, Jan E. Gerken, Klaus-Robert Müller, Pan Kessel:
Diffeomorphic Counterfactuals with Generative Models. CoRR abs/2206.05075 (2022) - [i106]Niklas Frederik Schmitz, Klaus-Robert Müller, Stefan Chmiela:
Algorithmic Differentiation for Automatized Modelling of Machine Learned Force Fields. CoRR abs/2208.12104 (2022) - [i105]Alexander Binder
Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations. CoRR abs/2211.12486 (2022) - [i104]Stefan Blücher, Klaus-Robert Müller, Stefan Chmiela:
Reconstructing Kernel-based Machine Learning Force Fields with Super-linear Convergence. CoRR abs/2212.12737 (2022) - [i103]Pattarawat Chormai, Jan Herrmann, Klaus-Robert Müller, Grégoire Montavon:
Disentangled Explanations of Neural Network Predictions by Finding Relevant Subspaces. CoRR abs/2212.14855 (2022) - 2021
- [j166]Mihail Bogojeski
Forecasting industrial aging processes with machine learning methods. Comput. Chem. Eng. 144: 107123 (2021) - [j165]Stefan Studer
Towards CRISP-ML(Q): A Machine Learning Process Model with Quality Assurance Methodology. Mach. Learn. Knowl. Extr. 3(2): 392-413 (2021) - [j164]Alexander Binder
Morphological and molecular breast cancer profiling through explainable machine learning. Nat. Mach. Intell. 3(4): 355-366 (2021) - [j163]Ali Hashemi, Chang Cai, Gitta Kutyniok
Unification of sparse Bayesian learning algorithms for electromagnetic brain imaging with the majorization minimization framework. NeuroImage 239: 118309 (2021) - [j162]Vignesh Srinivasan
Robustifying models against adversarial attacks by Langevin dynamics. Neural Networks 137: 1-17 (2021) - [j161]Wojciech Samek
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications. Proc. IEEE 109(3): 247-278 (2021) - [j160]Lukas Ruff
A Unifying Review of Deep and Shallow Anomaly Detection. Proc. IEEE 109(5): 756-795 (2021) - [j159]Kai J. Miller, Klaus-Robert Müller
Basis profile curve identification to understand electrical stimulation effects in human brain networks. PLoS Comput. Biol. 17(9) (2021) - [j158]Seul-Ki Yeom, Philipp Seegerer
Pruning by explaining: A novel criterion for deep neural network pruning. Pattern Recognit. 115: 107899 (2021) - [j157]Felix Sattler
Clustered Federated Learning: Model-Agnostic Distributed Multitask Optimization Under Privacy Constraints. IEEE Trans. Neural Networks Learn. Syst. 32(8): 3710-3722 (2021) - [c177]Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen
Explainable Deep One-Class Classification. ICLR 2021 - [c176]Oliver T. Unke, Mihail Bogojeski, Michael Gastegger, Mario Geiger, Tess E. Smidt
SE(3)-equivariant prediction of molecular wavefunctions and electronic densities. NeurIPS 2021: 14434-14447 - [c175]Ali Hashemi, Yijing Gao, Chang Cai, Sanjay Ghosh, Klaus-Robert Müller, Srikantan S. Nagarajan, Stefan Haufe:
Efficient hierarchical Bayesian inference for spatio-temporal regression models in neuroimaging. NeurIPS 2021: 24855-24870 - [i102]Oliver T. Unke, Stefan Chmiela, Michael Gastegger, Kristof T. Schütt, Huziel E. Sauceda, Klaus-Robert Müller:
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects. CoRR abs/2105.00304 (2021) - [i101]Danny Panknin, Shinichi Nakajima, Klaus-Robert Müller:
Optimal Sampling Density for Nonparametric Regression. CoRR abs/2105.11990 (2021) - [i100]Huziel E. Sauceda, Luis E. Gálvez-González, Stefan Chmiela, Lauro Oliver Paz-Borbón, Klaus-Robert Müller, Alexandre Tkatchenko:
BIGDML: Towards Exact Machine Learning Force Fields for Materials. CoRR abs/2106.04229 (2021) - [i99]Léo Andéol, Yusei Kawakami, Yuichiro Wada, Takafumi Kanamori, Klaus-Robert Müller, Grégoire Montavon:
Learning Domain Invariant Representations by Joint Wasserstein Distance Minimization. CoRR abs/2106.04923 (2021) - [i98]Christopher J. Anders, David Neumann, Wojciech Samek, Klaus-Robert Müller, Sebastian Lapuschkin:
Software for Dataset-wide XAI: From Local Explanations to Global Insights with Zennit, CoRelAy, and ViRelAy. CoRR abs/2106.13200 (2021) - [i97]Vignesh Srinivasan, Nils Strodthoff, Jackie Ma, Alexander Binder, Klaus-Robert Müller, Wojciech Samek:
On the Robustness of Pretraining and Self-Supervision for a Deep Learning-based Analysis of Diabetic Retinopathy. CoRR abs/2106.13497 (2021) - [i96]Kirill Bykov, Marina M.-C. Höhne, Adelaida Creosteanu, Klaus-Robert Müller, Frederick Klauschen, Shinichi Nakajima, Marius Kloft:
Explaining Bayesian Neural Networks. CoRR abs/2108.10346 (2021) - [i95]Niklas W. A. Gebauer, Michael Gastegger, Stefaan Simon Pierre Hessmann, Klaus-Robert Müller, Kristof T. Schütt:
Inverse design of 3d molecular structures with conditional generative neural networks. CoRR abs/2109.04824 (2021) - [i94]Armin W. Thomas, Ulman Lindenberger, Wojciech Samek, Klaus-Robert Müller:
Evaluating deep transfer learning for whole-brain cognitive decoding. CoRR abs/2111.01562 (2021) - [i93]Ali Hashemi, Yijing Gao, Chang Cai, Sanjay Ghosh, Klaus-Robert Müller, Srikantan S. Nagarajan, Stefan Haufe:
Efficient Hierarchical Bayesian Inference for Spatio-temporal Regression Models in Neuroimaging. CoRR abs/2111.01692 (2021) - [i92]Rick Wilming, Céline Budding, Klaus-Robert Müller, Stefan Haufe:
Scrutinizing XAI using linear ground-truth data with suppressor variables. CoRR abs/2111.07473 (2021) - [i91]Simon Letzgus, Patrick Wagner, Jonas Lederer, Wojciech Samek, Klaus-Robert Müller, Grégoire Montavon:
Toward Explainable AI for Regression Models. CoRR abs/2112.11407 (2021) - 2020
- [j156]Alexander von Lühmann
Improved physiological noise regression in fNIRS: A multimodal extension of the General Linear Model using temporally embedded Canonical Correlation Analysis. NeuroImage 208: 116472 (2020) - [j155]Mina Jamshidi Idaji
Nonlinear interaction decomposition (NID): A method for separation of cross-frequency coupled sources in human brain. NeuroImage 211: 116599 (2020) - [j154]Felix Sattler, Jackie Ma, Patrick Wagner, David Neumann
Risk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements. npj Digit. Medicine 3 (2020) - [j153]Jacob R. Kauffmann
Towards explaining anomalies: A deep Taylor decomposition of one-class models. Pattern Recognit. 101: 107198 (2020) - [j152]Dong-Ok Won
An adaptive deep reinforcement learning framework enables curling robots with human-like performance in real-world conditions. Sci. Robotics 5(46): 9764 (2020) - [j151]Tobias Kretz
Mammography Image Quality Assurance Using Deep Learning. IEEE Trans. Biomed. Eng. 67(12): 3317-3326 (2020) - [j150]Simon Wiedemann
Compact and Computationally Efficient Representation of Deep Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 31(3): 772-785 (2020) - [j149]Alexander Bauer
Optimizing for Measure of Performance in Max-Margin Parsing. IEEE Trans. Neural Networks Learn. Syst. 31(7): 2680-2684 (2020) - [j148]Felix Sattler
Robust and Communication-Efficient Federated Learning From Non-i.i.d. Data. IEEE Trans. Neural Networks Learn. Syst. 31(9): 3400-3413 (2020) - [c174]Vignesh Srinivasan, Klaus-Robert Müller
Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance. AAAI 2020: 5842-5850 - [c173]Klaus-Robert Müller:
Analysing the Changing Brain: Immediate Brain Plasticity After One Hour of BCI. BCI 2020: 1-2 - [c172]Felix Sattler, Klaus-Robert Müller
On the Byzantine Robustness of Clustered Federated Learning. ICASSP 2020: 8861-8865 - [c171]Tamer Ajaj, Klaus-Robert Müller
EEG-Based Assessment of Perceived Quality in Complex Natural Images. ICIP 2020: 136-140 - [c170]Lukas Ruff, Robert A. Vandermeulen
Deep Semi-Supervised Anomaly Detection. ICLR 2020 - [c169]Andreas Holzinger
xxAI - Beyond Explainable Artificial Intelligence. xxAI@ICML 2020: 3-10 - [c168]Grégoire Montavon
Explaining the Predictions of Unsupervised Learning Models. xxAI@ICML 2020: 117-138 - [c167]Christopher J. Anders, Plamen Pasliev, Ann-Kathrin Dombrowski, Klaus-Robert Müller, Pan Kessel:
Fairwashing explanations with off-manifold detergent. ICML 2020: 314-323 - [c166]Milena T. Bagdasarian
EEG-Based Assessment of Perceived Realness in Stylized Face Images. QoMEX 2020: 1-4 - [p27]Philipp Seegerer
Interpretable Deep Neural Network to Predict Estrogen Receptor Status from Haematoxylin-Eosin Images. AI and ML for Digital Pathology 2020: 16-37 - [i90]Mihail Bogojeski, Simeon Sauer, Franziska Horn, Klaus-Robert Müller:
Forecasting Industrial Aging Processes with Machine Learning Methods. CoRR abs/2002.01768 (2020) - [i89]Philipp Leinen, Malte Esders, Kristof T. Schütt, Christian Wagner, Klaus-Robert Müller, F. Stefan Tautz:
Autonomous robotic nanofabrication with reinforcement learning. CoRR abs/2002.11952 (2020) - [i88]Stefan Studer, Thanh Binh Bui, Christian Drescher, Alexander Hanuschkin, Ludwig Winkler, Steven Peters, Klaus-Robert Müller:
Towards CRISP-ML(Q): A Machine Learning Process Model with Quality Assurance Methodology. CoRR abs/2003.05155 (2020) - [i87]Oliver Eberle, Jochen Büttner, Florian Kräutli, Klaus-Robert Müller, Matteo Valleriani, Grégoire Montavon:
Building and Interpreting Deep Similarity Models. CoRR abs/2003.05431 (2020) - [i86]Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, Christopher J. Anders, Klaus-Robert Müller:
Toward Interpretable Machine Learning: Transparent Deep Neural Networks and Beyond. CoRR abs/2003.07631 (2020) - [i85]David Lassner, Anne Baillot, Sergej Dogadov, Klaus-Robert Müller, Shinichi Nakajima:
Automatic Identification of Types of Alterations in Historical Manuscripts. CoRR abs/2003.09136 (2020) - [i84]Felix Sattler, Jackie Ma, Patrick Wagner, David Neumann, Markus Wenzel, Ralf Schäfer, Wojciech Samek, Klaus-Robert Müller, Thomas Wiegand:
Risk Estimation of SARS-CoV-2 Transmission from Bluetooth Low Energy Measurements. CoRR abs/2004.11841 (2020) - [i83]Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Klaus-Robert Müller, Marius Kloft:
Rethinking Assumptions in Deep Anomaly Detection. CoRR abs/2006.00339 (2020) - [i82]Thomas Schnake, Oliver Eberle, Jonas Lederer, Shinichi Nakajima, Kristof T. Schütt, Klaus-Robert Müller, Grégoire Montavon:
XAI for Graphs: Explaining Graph Neural Network Predictions by Identifying Relevant Walks. CoRR abs/2006.03589 (2020) - [i81]Kirill Bykov, Marina M.-C. Höhne, Klaus-Robert Müller, Shinichi Nakajima, Marius Kloft:
How Much Can I Trust You? - Quantifying Uncertainties in Explaining Neural Networks. CoRR abs/2006.09000 (2020) - [i80]Jacob R. Kauffmann, Lukas Ruff, Grégoire Montavon, Klaus-Robert Müller:
The Clever Hans Effect in Anomaly Detection. CoRR abs/2006.10609 (2020) - [i79]Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Marius Kloft, Klaus-Robert Müller:
Explainable Deep One-Class Classification. CoRR abs/2007.01760 (2020) - [i78]Christopher J. Anders, Plamen Pasliev, Ann-Kathrin Dombrowski, Klaus-Robert Müller, Pan Kessel:
Fairwashing Explanations with Off-Manifold Detergent. CoRR abs/2007.09969 (2020) - [i77]Vignesh Srinivasan, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima:
Langevin Cooling for Domain Translation. CoRR abs/2008.13723 (2020) - [i76]Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, Klaus-Robert Müller:
A Unifying Review of Deep and Shallow Anomaly Detection. CoRR abs/2009.11732 (2020) - [i75]Ann-Kathrin Dombrowski, Christopher J. Anders, Klaus-Robert Müller, Pan Kessel:
Towards Robust Explanations for Deep Neural Networks. CoRR abs/2012.10425 (2020)
2010 – 2019
- 2019
- [j147]Guido Schwenk
Classification of structured validation data using stateless and stateful features. Comput. Commun. 138: 54-66 (2019) - [j146]Stefan Chmiela, Huziel Enoc Sauceda Felix, Igor Poltavsky, Klaus-Robert Müller
sGDML: Constructing accurate and data efficient molecular force fields using machine learning. Comput. Phys. Commun. 240: 38-45 (2019) - [j145]Sebastian Bosse
Estimation of distortion sensitivity for visual quality prediction using a convolutional neural network. Digit. Signal Process. 91: 54-65 (2019) - [j144]Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele, Kristof T. Schütt, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller, Sven Dähne, Pieter-Jan Kindermans:
iNNvestigate Neural Networks! J. Mach. Learn. Res. 20: 93:1-93:8 (2019) - [j143]Joey Tianyi Zhou
N-ary decomposition for multi-class classification. Mach. Learn. 108(5): 809-830 (2019) - [j142]Carmen Vidaurre
Enhancing sensorimotor BCI performance with assistive afferent activity: An online evaluation. NeuroImage 199: 375-386 (2019) - [j141]Alexander von Lühmann
A new blind source separation framework for signal analysis and artifact rejection in functional Near-Infrared Spectroscopy. NeuroImage 200: 72-88 (2019) - [j140]Carmen Vidaurre
Canonical maximization of coherence: A novel tool for investigation of neuronal interactions between two datasets. NeuroImage 201 (2019) - [c165]Alexander Bauer, Shinichi Nakajima, Nico Görnitz, Klaus-Robert Müller:
Partial Optimality of Dual Decomposition for MAP Inference in Pairwise MRFs. AISTATS 2019: 1696-1703 - [c164]Klaus-Robert Müller
Explainable Deep Learning for Analysing Brain Data. BCI 2019: 1-2 - [c163]Leila Arras
Evaluating Recurrent Neural Network Explanations. BlackboxNLP@ACL 2019: 113-126 - [c162]Patrick Wagner, Jakob Paul Morath, Arturo Zychlinsky, Klaus-Robert Müller
Rotation Invariant Clustering of 3D Cell Nuclei Shapes. EMBC 2019: 6022-6027 - [c161]Vignesh Srinivasan, Ercan E. Kuruoglu
Black-Box Decision based Adversarial Attack with Symmetric α-stable Distribution. EUSIPCO 2019: 1-5 - [c160]Felix Sattler, Simon Wiedemann
Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication. IJCNN 2019: 1-8 - [c159]Simon Wiedemann
Entropy-Constrained Training of Deep Neural Networks. IJCNN 2019: 1-8 - [c158]Armin W. Thomas
Deep Transfer Learning for Whole-Brain FMRI Analyses. OR/MLCN@MICCAI 2019: 59-67 - [c157]Sören Becker, Klaus-Robert Müller
A Neural Network Model of Spatial Distortion Sensitivity for Video Quality Estimation. MLSP 2019: 1-6 - [c156]Ann-Kathrin Dombrowski, Maximilian Alber, Christopher J. Anders, Marcel Ackermann, Klaus-Robert Müller, Pan Kessel:
Explanations can be manipulated and geometry is to blame. NeurIPS 2019: 13567-13578 - [p26]Wojciech Samek
Towards Explainable Artificial Intelligence. Explainable AI 2019: 5-22 - [p25]Grégoire Montavon, Alexander Binder
Layer-Wise Relevance Propagation: An Overview. Explainable AI 2019: 193-209 - [p24]Leila Arras
Explaining and Interpreting LSTMs. Explainable AI 2019: 211-238 - [p23]Christopher J. Anders
Understanding Patch-Based Learning of Video Data by Explaining Predictions. Explainable AI 2019: 297-309 - [p22]Kristof T. Schütt, Michael Gastegger, Alexandre Tkatchenko, Klaus-Robert Müller:
Quantum-Chemical Insights from Interpretable Atomistic Neural Networks. Explainable AI 2019: 311-330 - [p21]David Hübner, Pieter-Jan Kindermans, Thibault Verhoeven, Klaus-Robert Müller, Michael Tangermann:
Rethinking BCI Paradigm and Machine Learning Algorithm as a Symbiosis: Zero Calibration, Guaranteed Convergence and High Decoding Performance. Brain-Computer Interface Research (7) 2019: 63-73 - [e5]Wojciech Samek, Grégoire Montavon, Andrea Vedaldi, Lars Kai Hansen
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning. Lecture Notes in Computer Science 11700, Springer 2019, ISBN 978-3-030-28953-9 [contents] - [i74]Lea Helmers, Franziska Horn, Franziska Biegler, Tim Oppermann, Klaus-Robert Müller:
Automating the search for a patent's prior art with a full text similarity search. CoRR abs/1901.03136 (2019) - [i73]Sebastian Lapuschkin, Stephan Wäldchen, Alexander Binder, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller:
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn. CoRR abs/1902.10178 (2019) - [i72]Danny Panknin, Shinichi Nakajima, Thanh Binh Bui, Klaus-Robert Müller:
Local Bandwidth Estimation via Mixture of Gaussian Processes. CoRR abs/1902.10664 (2019) - [i71]Felix Sattler, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek:
Robust and Communication-Efficient Federated Learning from Non-IID Data. CoRR abs/1903.02891 (2019) - [i70]Kim Nicoli
Comment on "Solving Statistical Mechanics Using VANs": Introducing saVANt - VANs Enhanced by Importance and MCMC Sampling. CoRR abs/1903.11048 (2019) - [i69]Vignesh Srinivasan, Ercan E. Kuruoglu, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima:
Black-Box Decision based Adversarial Attack with Symmetric α-stable Distribution. CoRR abs/1904.05586 (2019) - [i68]Leila Arras, Ahmed Osman, Klaus-Robert Müller, Wojciech Samek:
Evaluating Recurrent Neural Network Explanations. CoRR abs/1904.11829 (2019) - [i67]Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, Klaus-Robert Müller, Marius Kloft:
Deep Semi-Supervised Anomaly Detection. CoRR abs/1906.02694 (2019) - [i66]Jacob R. Kauffmann, Malte Esders, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller:
From Clustering to Cluster Explanations via Neural Networks. CoRR abs/1906.07633 (2019) - [i65]Ann-Kathrin Dombrowski, Maximilian Alber, Christopher J. Anders, Marcel Ackermann, Klaus-Robert Müller, Pan Kessel:
Explanations can be manipulated and geometry is to blame. CoRR abs/1906.07983 (2019) - [i64]Armin W. Thomas
Deep Transfer Learning For Whole-Brain fMRI Analyses. CoRR abs/1907.01953 (2019) - [i63]Miriam Hägele, Philipp Seegerer
Resolving challenges in deep learning-based analyses of histopathological images using explanation methods. CoRR abs/1908.06943 (2019) - [i62]Wojciech Samek, Klaus-Robert Müller:
Towards Explainable Artificial Intelligence. CoRR abs/1909.12072 (2019) - [i61]Leila Arras, Jose A. Arjona-Medina, Michael Widrich, Grégoire Montavon, Michael Gillhofer, Klaus-Robert Müller, Sepp Hochreiter
Explaining and Interpreting LSTMs. CoRR abs/1909.12114 (2019) - [i60]Felix Sattler, Klaus-Robert Müller, Wojciech Samek:
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints. CoRR abs/1910.01991 (2019) - [i59]Kim A. Nicoli
Asymptotically Unbiased Generative Neural Sampling. CoRR abs/1910.13496 (2019) - [i58]Frank Noé, Alexandre Tkatchenko, Klaus-Robert Müller, Cecilia Clementi:
Machine learning for molecular simulation. CoRR abs/1911.02792 (2019) - [i57]Seul-Ki Yeom, Philipp Seegerer, Sebastian Lapuschkin
Pruning by Explaining: A Novel Criterion for Deep Neural Network Pruning. CoRR abs/1912.08881 (2019) - [i56]Christopher J. Anders, Talmaj Marinc, David Neumann, Wojciech Samek, Klaus-Robert Müller, Sebastian Lapuschkin
Analyzing ImageNet with Spectral Relevance Analysis: Towards ImageNet un-Hans'ed. CoRR abs/1912.11425 (2019) - 2018
- [j139]David Hübner, Thibault Verhoeven, Klaus-Robert Müller
Unsupervised Learning for Brain-Computer Interfaces Based on Event-Related Potentials: Review and Online Comparison [Research Frontier]. IEEE Comput. Intell. Mag. 13(2): 66-67 (2018) - [j138]Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
Methods for interpreting and understanding deep neural networks. Digit. Signal Process. 73: 1-15 (2018) - [j137]Stephan Kaltenstadler, Shinichi Nakajima
Wasserstein Stationary Subspace Analysis. IEEE J. Sel. Top. Signal Process. 12(6): 1213-1223 (2018) - [j136]Jaeyoung Shin
Improvement of Information Transfer Rates Using a Hybrid EEG-NIRS Brain-Computer Interface with a Short Trial Length: Offline and Pseudo-Online Analyses. Sensors 18(6): 1827 (2018) - [j135]Sebastian Bosse
Assessing Perceived Image Quality Using Steady-State Visual Evoked Potentials and Spatio-Spectral Decomposition. IEEE Trans. Circuits Syst. Video Technol. 28(8): 1694-1706 (2018) - [j134]Sebastian Bosse
Deep Neural Networks for No-Reference and Full-Reference Image Quality Assessment. IEEE Trans. Image Process. 27(1): 206-219 (2018) - [j133]Nico Görnitz
Transductive Regression for Data With Latent Dependence Structure. IEEE Trans. Neural Networks Learn. Syst. 29(7): 2743-2756 (2018) - [j132]Nico Görnitz
Support Vector Data Descriptions and k-Means Clustering: One Class? IEEE Trans. Neural Networks Learn. Syst. 29(9): 3994-4006 (2018) - [c155]Klaus-Robert Müller
Towards robust machine learning methods for the analysis of brain data. BCI 2018: 1-2 - [c154]Jaeyoung Shin, Alexander von Lühmann
Open access repository for hybrid EEG-NIRS data. BCI 2018: 1-4 - [c153]Masahiro Yukawa, Klaus-Robert Müller
How are the Centered Kernel Principal Components Relevant to Regression Task? -An Exact Analysis. ICASSP 2018: 2841-2845 - [c152]Pieter-Jan Kindermans, Kristof T. Schütt, Maximilian Alber, Klaus-Robert Müller, Dumitru Erhan, Been Kim, Sven Dähne:
Learning how to explain neural networks: PatternNet and PatternAttribution. ICLR (Poster) 2018 - [c151]Dong-Ok Won, Byung-Do Kim, Ho-Jung Kim, Tae-San Eom
Curly: An AI-based Curling Robot Successfully Competing in the Olympic Discipline of Curling. IJCAI 2018: 5883-5885 - [i55]Jacob R. Kauffmann, Klaus-Robert Müller, Grégoire Montavon:
Towards Explaining Anomalies: A Deep Taylor Decomposition of One-Class Models. CoRR abs/1805.06230 (2018) - [i54]Felix Sattler, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek:
Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication. CoRR abs/1805.08768 (2018) - [i53]Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek:
Compact and Computationally Efficient Representation of Deep Neural Networks. CoRR abs/1805.10692 (2018) - [i52]Alexander Binder
Towards computational fluorescence microscopy: Machine learning-based integrated prediction of morphological and molecular tumor profiles. CoRR abs/1805.11178 (2018) - [i51]Vignesh Srinivasan, Arturo Marbán, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima:
Counterstrike: Defending Deep Learning Architectures Against Adversarial Samples by Langevin Dynamics with Supervised Denoising Autoencoder. CoRR abs/1805.12017 (2018) - [i50]Hannah Marienwald, Wikor Pronobis, Klaus-Robert Müller, Shinichi Nakajima:
Tight Bound of Incremental Cover Trees for Dynamic Diversification. CoRR abs/1806.06126 (2018) - [i49]Christopher J. Anders, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller:
Understanding Patch-Based Learning by Explaining Predictions. CoRR abs/1806.06926 (2018) - [i48]Kristof T. Schütt, Michael Gastegger, Alexandre Tkatchenko, Klaus-Robert Müller:
Quantum-chemical insights from interpretable atomistic neural networks. CoRR abs/1806.10349 (2018) - [i47]Jacob R. Kauffmann, Grégoire Montavon, Luiz Alberto Lima, Shinichi Nakajima, Klaus-Robert Müller, Nico Görnitz:
Unsupervised Detection and Explanation of Latent-class Contextual Anomalies. CoRR abs/1806.11326 (2018) - [i46]Sören Becker, Marcel Ackermann, Sebastian Lapuschkin, Klaus-Robert Müller, Wojciech Samek:
Interpreting and Explaining Deep Neural Networks for Classification of Audio Signals. CoRR abs/1807.03418 (2018) - [i45]Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele, Kristof T. Schütt, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller, Sven Dähne, Pieter-Jan Kindermans:
iNNvestigate neural networks! CoRR abs/1808.04260 (2018) - [i44]Fabian Horst, Sebastian Lapuschkin, Wojciech Samek, Klaus-Robert Müller, Wolfgang Immanuel Schöllhorn:
What is Unique in Individual Gait Patterns? Understanding and Interpreting Deep Learning in Gait Analysis. CoRR abs/1808.04308 (2018) - [i43]Armin W. Thomas
Interpretable LSTMs For Whole-Brain Neuroimaging Analyses. CoRR abs/1810.09945 (2018) - [i42]Kristof T. Schütt, Alexandre Tkatchenko, Klaus-Robert Müller:
Learning representations of molecules and materials with atomistic neural networks. CoRR abs/1812.04690 (2018) - [i41]Simon Wiedemann, Arturo Marbán, Klaus-Robert Müller, Wojciech Samek:
Entropy-Constrained Training of Deep Neural Networks. CoRR abs/1812.07520 (2018) - 2017
- [j131]Luiz Alberto Lima, Nico Görnitz, Luiz Eduardo Varella, Marley M. B. R. Vellasco
Porosity estimation by semi-supervised learning with sparsely available labeled samples. Comput. Geosci. 106: 33-48 (2017) - [j130]Weiwei Liu, Ivor W. Tsang
An Easy-to-hard Learning Paradigm for Multiple Classes and Multiple Labels. J. Mach. Learn. Res. 18: 94:1-94:38 (2017) - [j129]Grégoire Montavon, Sebastian Lapuschkin
Explaining nonlinear classification decisions with deep Taylor decomposition. Pattern Recognit. 65: 211-222 (2017) - [j128]Alexander von Lühmann
M3BA: A Mobile, Modular, Multimodal Biosignal Acquisition Architecture for Miniaturized EEG-NIRS-Based Hybrid BCI and Monitoring. IEEE Trans. Biomed. Eng. 64(6): 1199-1210 (2017) - [j127]Alexander Bauer, Mikio L. Braun, Klaus-Robert Müller
Accurate Maximum-Margin Training for Parsing With Context-Free Grammars. IEEE Trans. Neural Networks Learn. Syst. 28(1): 44-56 (2017) - [j126]Alexander Bauer
Efficient Exact Inference With Loss Augmented Objective in Structured Learning. IEEE Trans. Neural Networks Learn. Syst. 28(11): 2566-2579 (2017) - [j125]Wojciech Samek
Evaluating the Visualization of What a Deep Neural Network Has Learned. IEEE Trans. Neural Networks Learn. Syst. 28(11): 2660-2673 (2017) - [c150]Jaeyoung Shin, Klaus-Robert Müller
Hybrid EEG-NIRS brain-computer interface under eyes-closed condition. APSIPA 2017: 721-723 - [c149]Seong-Whan Lee, Klaus-Robert Müller:
Welcome message from the general chairs. BCI 2017: 1 - [c148]Dong-Ok Won, Han-Jeong Hwang, Klaus-Robert Müller
Shifting stimuli for brain computer interface based on rapid serial visual presentation. BCI 2017: 40-41 - [c147]Klaus-Robert Müller
From measurement to machine learning: Towards analysing cognition. BCI 2017: 53-54 - [c146]Jing Yu Koh, Wojciech Samek, Klaus-Robert Müller
Object Boundary Detection and Classification with Image-Level Labels. GCPR 2017: 153-164 - [c145]Alexander von Lühmann
Why build an integrated EEG-NIRS? About the advantages of hybrid bio-acquisition hardware. EMBC 2017: 4475-4478 - [c144]Andrea Kübler, Klaus-Robert Müller
The P300 BCI: on its Way to End-Users? GBCIC 2017 - [c143]Alexander von Lühmann, Surjo R. Soekadar, Benjamin Blankertz, Klaus-Robert Müller
Headgear for Mobile Neurotechnology: looking into Alternatives for EEG and NIRS probes. GBCIC 2017 - [c142]Dong-Ok Won, Han-Jeong Hwang, Klaus-Robert Müller
Improving Classification Performance of a brain-Computer Interface System based on Rapid Serial Visual Presentation by Shifting stimuli. GBCIC 2017 - [c141]Vignesh Srinivasan, Sebastian Lapuschkin
Interpretable human action recognition in compressed domain. ICASSP 2017: 1692-1696 - [c140]Wojciech Samek, Alexander Binder
Understanding and Comparing Deep Neural Networks for Age and Gender Classification. ICCV Workshops 2017: 1629-1638 - [c139]János Höner, Shinichi Nakajima, Alexander Bauer, Klaus-Robert Müller, Nico Görnitz:
Minimizing Trust Leaks for Robust Sybil Detection. ICML 2017: 1520-1528 - [c138]Philipp Helle, Heiko Schwarz, Thomas Wiegand, Klaus-Robert Müller
Reinforcement learning for video encoder control in HEVC. IWSSIP 2017: 1-5 - [c137]Kristof Schütt, Pieter-Jan Kindermans, Huziel Enoc Sauceda Felix, Stefan Chmiela, Alexandre Tkatchenko, Klaus-Robert Müller:
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions. NIPS 2017: 991-1001 - [c136]Maximilian Alber, Pieter-Jan Kindermans, Kristof Schütt, Klaus-Robert Müller, Fei Sha:
An Empirical Study on The Properties of Random Bases for Kernel Methods. NIPS 2017: 2763-2774 - [c135]Leila Arras
Explaining Recurrent Neural Network Predictions in Sentiment Analysis. WASSA@EMNLP 2017: 159-168 - [i40]David Hübner, Thibault Verhoeven, Konstantin Schmid, Klaus-Robert Müller, Michael Tangermann, Pieter-Jan Kindermans:
Learning from Label Proportions in Brain-Computer Interfaces: Online Unsupervised Learning with Guarantees. CoRR abs/1701.07213 (2017) - [i39]Franziska Horn, Klaus-Robert Müller:
Learning similarity preserving representations with neural similarity encoders. CoRR abs/1702.01824 (2017) - [i38]Pieter-Jan Kindermans, Kristof T. Schütt, Maximilian Alber, Klaus-Robert Müller, Sven Dähne:
PatternNet and PatternLRP - Improving the interpretability of neural networks. CoRR abs/1705.05598 (2017) - [i37]Leila Arras, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Explaining Recurrent Neural Network Predictions in Sentiment Analysis. CoRR abs/1706.07206 (2017) - [i36]Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller:
Methods for Interpreting and Understanding Deep Neural Networks. CoRR abs/1706.07979 (2017) - [i35]Franziska Horn, Leila Arras, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Exploring text datasets by visualizing relevant words. CoRR abs/1707.05261 (2017) - [i34]Franziska Horn, Leila Arras, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Discovering topics in text datasets by visualizing relevant words. CoRR abs/1707.06100 (2017) - [i33]Alexander Bauer, Shinichi Nakajima, Nico Görnitz, Klaus-Robert Müller:
Partial Optimality of Dual Decomposition for MAP Inference in Pairwise MRFs. CoRR abs/1708.03314 (2017) - [i32]Sebastian Lapuschkin, Alexander Binder, Klaus-Robert Müller, Wojciech Samek:
Understanding and Comparing Deep Neural Networks for Age and Gender Classification. CoRR abs/1708.07689 (2017) - [i31]Wojciech Samek, Thomas Wiegand, Klaus-Robert Müller:
Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models. CoRR abs/1708.08296 (2017) - [i30]Alexander Bauer, Shinichi Nakajima, Nico Görnitz, Klaus-Robert Müller:
Optimizing for Measure of Performance in Max-Margin Parsing. CoRR abs/1709.01562 (2017) - 2016
- [j124]Sebastian Lapuschkin, Alexander Binder, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
The LRP Toolbox for Artificial Neural Networks. J. Mach. Learn. Res. 17: 114:1-114:5 (2016) - [j123]Johannes Höhne, Daniel Bartz, Martin N. Hebart
Analyzing neuroimaging data with subclasses: A shrinkage approach. NeuroImage 124: 740-751 (2016) - [j122]Matthias Sebastian Treder, Anne K. Porbadnigk, Forooz Shahbazi Avarvand, Klaus-Robert Müller
The LDA beamformer: Optimal estimation of ERP source time series using linear discriminant analysis. NeuroImage 129: 279-291 (2016) - [j121]Wojciech Samek, Duncan A. J. Blythe, Gabriel Curio
Multiscale temporal neural dynamics predict performance in a complex sensorimotor task. NeuroImage 141: 291-303 (2016) - [j120]Masahiro Yukawa, Klaus-Robert Müller
Why Does a Hilbertian Metric Work Efficiently in Online Learning With Kernels? IEEE Signal Process. Lett. 23(10): 1424-1428 (2016) - [j119]Irene Winkler
Validity of Time Reversal for Testing Granger Causality. IEEE Trans. Signal Process. 64(11): 2746-2760 (2016) - [c134]Klaus-Robert Müller
Machine learning for BCI: towards analysing cognition. BCI 2016: 1-2 - [c133]Sebastian Lapuschkin
Analyzing Classifiers: Fisher Vectors and Deep Neural Networks. CVPR 2016: 2912-2920 - [c132]Farhad Arbabzadah, Grégoire Montavon, Klaus-Robert Müller
Identifying Individual Facial Expressions by Deconstructing a Neural Network. GCPR 2016: 344-354 - [c131]Airi Takeuchi, Masahiro Yukawa, Klaus-Robert Müller
A better metric in kernel adaptive filtering. EUSIPCO 2016: 1578-1582 - [c130]Alexander Binder
Layer-Wise Relevance Propagation for Neural Networks with Local Renormalization Layers. ICANN (2) 2016: 63-71 - [c129]Sebastian Bach
Controlling explanatory heatmap resolution and semantics via decomposition depth. ICIP 2016: 2271-2275 - [c128]Grégoire Montavon, Klaus-Robert Müller, Marco Cuturi:
Wasserstein Training of Restricted Boltzmann Machines. NIPS 2016: 3711-3719 - [c127]Sebastian Bosse, Dominique Maniry, Klaus-Robert Müller
Neural network-based full-reference image quality assessment. PCS 2016: 1-5 - [c126]Santiago De-Luxán-Hernández
Block adaptive selection of multiple core transforms for video coding. PCS 2016: 1-5 - [c125]Leila Arras
Explaining Predictions of Non-Linear Classifiers in NLP. Rep4NLP@ACL 2016: 1-7 - [c124]Sebastian Bosse, Klaus-Robert Müller
Brain-Computer Interfacing for multimedia quality assessment. SMC 2016: 2834-2839 - [c123]Stephanie Brandl, Klaus-Robert Müller
Alternative CSP approaches for multimodal distributed BCI data. SMC 2016: 3742-3747 - [i29]Joey Tianyi Zhou, Ivor W. Tsang, Shen-Shyang Ho, Klaus-Robert Müller:
N-ary Error Correcting Coding Scheme. CoRR abs/1603.05850 (2016) - [i28]Sebastian Bach, Alexander Binder, Klaus-Robert Müller, Wojciech Samek:
Controlling Explanatory Heatmap Resolution and Semantics via Decomposition Depth. CoRR abs/1603.06463 (2016) - [i27]Alexander Binder, Grégoire Montavon, Sebastian Bach, Klaus-Robert Müller, Wojciech Samek:
Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers. CoRR abs/1604.00825 (2016) - [i26]Irene Sturm, Sebastian Bach, Wojciech Samek, Klaus-Robert Müller:
Interpretable Deep Neural Networks for Single-Trial EEG Classification. CoRR abs/1604.08201 (2016) - [i25]Farhad Arbabzadah, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Identifying individual facial expressions by deconstructing a neural network. CoRR abs/1606.07285 (2016) - [i24]Leila Arras, Franziska Horn, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Explaining Predictions of Non-Linear Classifiers in NLP. CoRR abs/1606.07298 (2016) - [i23]Jing Yu Koh, Wojciech Samek, Klaus-Robert Müller, Alexander Binder:
Zero Shot Learning for Semantic Boundary Detection - How Far Can We Get? CoRR abs/1606.09187 (2016) - [i22]Ivana Balazevic, Mikio Ludwig Braun, Klaus-Robert Müller:
Language Detection For Short Text Messages In Social Media. CoRR abs/1608.08515 (2016) - [i21]Felix Brockherde, Li Li, Kieron Burke, Klaus-Robert Müller:
By-passing the Kohn-Sham equations with machine learning. CoRR abs/1609.02815 (2016) - [i20]Wikor Pronobis, Danny Panknin, Johannes Kirschnick, Vignesh Srinivasan, Wojciech Samek, Volker Markl, Manohar Kaul
Sharing Hash Codes for Multiple Purposes. CoRR abs/1609.03219 (2016) - [i19]Pieter-Jan Kindermans, Kristof Schütt, Klaus-Robert Müller, Sven Dähne:
Investigating the influence of noise and distractors on the interpretation of neural networks. CoRR abs/1611.07270 (2016) - [i18]Marina M.-C. Vidovic, Nico Görnitz, Klaus-Robert Müller, Marius Kloft:
Feature Importance Measure for Non-linear Learning Algorithms. CoRR abs/1611.07567 (2016) - [i17]Wojciech Samek, Grégoire Montavon, Alexander Binder, Sebastian Lapuschkin, Klaus-Robert Müller:
Interpreting the Predictions of Complex ML Models by Layer-wise Relevance Propagation. CoRR abs/1611.08191 (2016) - [i16]Sebastian Bosse, Dominique Maniry, Klaus-Robert Müller, Thomas Wiegand, Wojciech Samek:
Deep Neural Networks for No-Reference and Full-Reference Image Quality Assessment. CoRR abs/1612.01697 (2016) - [i15]Leila Arras, Franziska Horn, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
"What is Relevant in a Text Document?": An Interpretable Machine Learning Approach. CoRR abs/1612.07843 (2016) - 2015
- [j118]Irene Winkler, Stefan Haufe
Identifying Granger causal relationships between neural power dynamics and variables of interest. NeuroImage 111: 489-504 (2015) - [j117]Anne K. Porbadnigk, Nico Görnitz, Claudia Sannelli, Alexander Binder
Extracting latent brain states - Towards true labels in cognitive neuroscience experiments. NeuroImage 120: 225-253 (2015) - [j116]Gernot R. Müller-Putz, José del R. Millán
The Plurality of Human Brain-Computer Interfacing [Scanning the Issue]. Proc. IEEE 103(6): 868-870 (2015) - [j115]Siamac Fazli
Learning From More Than One Data Source: Data Fusion Techniques for Sensorimotor Rhythm-Based Brain-Computer Interfaces. Proc. IEEE 103(6): 891-906 (2015) - [j114]Gernot R. Müller-Putz, Robert Leeb, Michael Tangermann, Johannes Höhne, Andrea Kübler, Febo Cincotti
Towards Noninvasive Hybrid Brain-Computer Interfaces: Framework, Practice, Clinical Application, and Beyond. Proc. IEEE 103(6): 926-943 (2015) - [j113]Sven Dähne, Felix Bießmann, Wojciech Samek, Stefan Haufe
Multivariate Machine Learning Methods for Fusing Multimodal Functional Neuroimaging Data. Proc. IEEE 103(9): 1507-1530 (2015) - [c122]Stephanie Brandl, Klaus-Robert Müller
Robust common spatial patterns based on Bhattacharyya distance and Gamma divergence. BCI 2015: 1-4 - [c121]Klaus-Robert Müller
Machine learning and BCI. BCI 2015: 1 - [c120]Jeong-Seok Woo, Klaus-Robert Müller
Classifying directions in continuous arm movement from EEG signals. BCI 2015: 1-2 - [c119]Laura Frølich, Irene Winkler, Klaus-Robert Müller
Investigating effects of different artefact types on motor imagery BCI. EMBC 2015: 1942-1945 - [c118]Irene Winkler, Stefan Debener
On the influence of high-pass filtering on ICA-based artifact reduction in EEG-ERP. EMBC 2015: 4101-4105 - [c117]Wojciech Samek, Klaus-Robert Müller
Tackling noise, artifacts and nonstationarity in BCI with robust divergences. EUSIPCO 2015: 2741-2745 - [c116]Santiago De-Luxán-Hernández
A kernel-based statistical analysis of the residual error in video coding. IWSSIP 2015: 192-195 - [c115]Stephanie Brandl, Johannes Höhne, Klaus-Robert Müller
Bringing BCI into everyday life: Motor imagery in a pseudo realistic environment. NER 2015: 224-227 - [c114]Marina M.-C. Vidovic, Nico Görnitz, Klaus-Robert Müller
Opening the Black Box: Revealing Interpretable Sequence Motifs in Kernel-Based Learning Algorithms. ECML/PKDD (2) 2015: 137-153 - [c113]Sofie Therese Hansen
Fusing Simultaneous EEG and fMRI Using Functional and Anatomical Information. PRNI 2015: 33-36 - [i14]Kevin Vu, John C. Snyder, Li Li, Matthias Rupp, Brandon F. Chen, Tarek Khelif, Klaus-Robert Müller, Kieron Burke:
Understanding Kernel Ridge Regression: Common behaviors from simple functions to density functionals. CoRR abs/1501.03854 (2015) - [i13]Grégoire Montavon, Klaus-Robert Müller, Marco Cuturi:
Wasserstein Training of Boltzmann Machines. CoRR abs/1507.01972 (2015) - [i12]Wojciech Samek, Alexander Binder, Grégoire Montavon, Sebastian Bach, Klaus-Robert Müller:
Evaluating the visualization of what a Deep Neural Network has learned. CoRR abs/1509.06321 (2015) - [i11]Sebastian Bach, Alexander Binder, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Analyzing Classifiers: Fisher Vectors and Deep Neural Networks. CoRR abs/1512.00172 (2015) - [i10]Grégoire Montavon, Sebastian Bach, Alexander Binder, Wojciech Samek, Klaus-Robert Müller:
Explaining NonLinear Classification Decisions with Deep Taylor Decomposition. CoRR abs/1512.02479 (2015) - 2014
- [j112]Motoaki Kawanabe, Wojciech Samek, Klaus-Robert Müller
Robust Common Spatial Filters with a Maxmin Approach. Neural Comput. 26(2): 349-376 (2014) - [j111]Sven Dähne, Frank C. Meinecke, Stefan Haufe
SPoC: A novel framework for relating the amplitude of neuronal oscillations to behaviorally relevant parameters. NeuroImage 86: 111-122 (2014) - [j110]Sven Dähne, Vadim V. Nikulin
Finding brain oscillations with power dependencies in neuroimaging data. NeuroImage 96: 334-348 (2014) - [j109]Duncan A. J. Blythe, Stefan Haufe
The effect of linear mixing in the EEG on Hurst exponent estimation. NeuroImage 99: 377-387 (2014) - [j108]Michael Gaebler
Stereoscopic depth increases intersubject correlations of brain networks. NeuroImage 100: 427-434 (2014) - [j107]Alexander Bauer, Nico Görnitz, Franziska Biegler, Klaus-Robert Müller
Efficient Algorithms for Exact Inference in Sequence Labeling SVMs. IEEE Trans. Neural Networks Learn. Syst. 25(5): 870-881 (2014) - [c112]Nico Görnitz, Anne Porbadnigk, Alexander Binder, Claudia Sannelli, Mikio L. Braun, Klaus-Robert Müller, Marius Kloft:
Learning and Evaluation in Presence of Non-i.i.d. Label Noise. AISTATS 2014: 293-302 - [c111]Sven Dähne, Felix Bießmann, Frank C. Meinecke, Jan Mehnert, Siamac Fazli
Multimodal integration of electrophysiological and hemodynamic signals. BCI 2014: 1-4 - [c110]Han-Jeong Hwang, Janne Mathias Hahne, Klaus-Robert Müller:
Channel selection for simultaneous myoelectric prosthesis control. BCI 2014: 1-4 - [c109]No-Sang Kwak, Klaus-Robert Müller, Seong-Whan Lee:
Toward exoskeleton control based on steady state visual evoked potentials. BCI 2014: 1-2 - [c108]Klaus-Robert Müller:
Multimodal imaging, non-stationarity and BCI. BCI 2014: 1 - [c107]Anne K. Porbadnigk, Nico Görnitz, Claudia Sannelli, Alexander Binder
When brain and behavior disagree: Tackling systematic label noise in EEG data with machine learning. BCI 2014: 1-4 - [c106]Wojciech Samek, Klaus-Robert Müller:
Information geometry meets BCI spatial filtering using divergences. BCI 2014: 1-4 - [c105]Seul-Ki Yeom, Siamac Fazli
Towards an enhanced ERP speller based on the visual processing of face familiarity. EMBC 2014: 1330-1333 - [c104]Marina M.-C. Vidovic, Liliana P. Paredes, Han-Jeong Hwang, Sebastian Amsüss, Jaspar Pahl, Janne Mathias Hahne, Bernhard Graimann, Dario Farina, Klaus-Robert Müller
Covariate shift adaptation in EMG pattern recognition for prosthetic device control. EMBC 2014: 4370-4373 - [c103]Sebastian Bosse, Laura Acqualagna, Anne K. Porbadnigk, Benjamin Blankertz, Gabriel Curio
Neurally informed assessment of perceived natural texture image quality. ICIP 2014: 1987-1991 - [c102]Daniel Bartz, Klaus-Robert Müller:
Covariance shrinkage for autocorrelated data. NIPS 2014: 1592-1600 - [c101]Felix Bießmann, Michael Gaebler, Jan-Peter Lamke, Ui Jong Ju
Data-driven multisubject neuroimaging analyses for naturalistic stimuli. PRNI 2014: 1-4 - [c100]Sven Dähne, Vadim V. Nikulin, David Ramírez
Optimizing spatial filters for the extraction of envelope-coupled neural oscillations. PRNI 2014: 1-4 - [c99]Johannes Höhne, Benjamin Blankertz, Klaus-Robert Müller
Mean shrinkage improves the classification of ERP signals by exploiting additional label information. PRNI 2014: 1-4 - [p20]Alexander Binder
Machine Learning for Visual Concept Recognition and Ranking for Images. Towards the Internet of Services 2014: 211-223 - [i9]Li Li, John C. Snyder, Isabelle M. Pelaschier, Jessica Huang, Uma-Naresh Niranjan, Paul Duncan, Matthias Rupp, Klaus-Robert Müller, Kieron Burke:
Understanding Machine-learned Density Functionals. CoRR abs/1404.1333 (2014) - [i8]Franz J. Király, Andreas Ziehe, Klaus-Robert Müller:
Learning with Algebraic Invariances, and the Invariant Kernel Trick. CoRR abs/1411.7817 (2014) - 2013
- [j106]Alexander Binder
Enhanced representation and multi-task learning for image annotation. Comput. Vis. Image Underst. 117(5): 466-478 (2013) - [j105]Anne Porbadnigk, Nico Görnitz, Marius Kloft, Klaus-Robert Müller
Decoding Brain States during Auditory Perception by Supervising Unsupervised Learning. J. Comput. Sci. Eng. 7(2): 112-121 (2013) - [j104]Stefan Haufe
A critical assessment of connectivity measures for EEG data: A simulation study. NeuroImage 64: 120-133 (2013) - [j103]Klaus-Robert Müller
Special Issue on Advances in Kernel-Based Learning for Signal Processing [From the Guest Editors]. IEEE Signal Process. Mag. 30(4): 14-15 (2013) - [j102]Grégoire Montavon, Mikio L. Braun, Tammo Krueger, Klaus-Robert Müller
Analyzing Local Structure in Kernel-Based Learning: Explanation, Complexity, and Reliability Assessment. IEEE Signal Process. Mag. 30(4): 62-74 (2013) - [j101]Wojciech Samek, Frank C. Meinecke, Klaus-Robert Müller
Transferring Subspaces Between Subjects in Brain-Computer Interfacing. IEEE Trans. Biomed. Eng. 60(8): 2289-2298 (2013) - [j100]Sven Dähne, Felix Bießmann, Frank C. Meinecke, Jan Mehnert
Integration of Multivariate Data Streams With Bandpower Signals. IEEE Trans. Multim. 15(5): 1001-1013 (2013) - [c98]Siamac Fazli
Tutorial on multimodal neuroimaging for brain-computer interfacing. BCI 2013: 1-2 - [c97]Anne K. Porbadnigk, Matthias Sebastian Treder, Siamac Fazli
Decoding cognitive brain states. BCI 2013: 16-18 - [c96]Seul-Ki Yeom, Siamac Fazli
Multimodal imaging technique for rapid response brain-computer interface feedback. BCI 2013: 92-94 - [c95]John C. Snyder, Sebastian Mika, Kieron Burke, Klaus-Robert Müller:
Kernels, Pre-images and Optimization. Empirical Inference 2013: 245-259 - [c94]Wojciech Samek, Alexander Binder
Multiple Kernel Learning for Brain-Computer Interfacing. EMBC 2013: 7048-7051 - [c93]Wojciech Samek, Duncan A. J. Blythe, Klaus-Robert Müller, Motoaki Kawanabe:
Robust Spatial Filtering with Beta Divergence. NIPS 2013: 1007-1015 - [c92]Daniel Bartz, Klaus-Robert Müller:
Generalizing Analytic Shrinkage for Arbitrary Covariance Structures. NIPS 2013: 1869-1877 - 2012
- [j99]Alexander Binder
On Taxonomies for Multi-class Image Categorization. Int. J. Comput. Vis. 99(3): 281-301 (2012) - [j98]Matthias Rupp, Alexandre Tkatchenko, Klaus-Robert Müller
Modeling of molecular atomization energies using machine learning. J. Cheminformatics 4(S-1): 33 (2012) - [j97]Franz J. Király, Paul von Bünau, Frank C. Meinecke, Duncan A. J. Blythe, Klaus-Robert Müller:
Algebraic Geometric Comparison of Probability Distributions. J. Mach. Learn. Res. 13: 855-903 (2012) - [j96]Siamac Fazli
Enhanced performance by a hybrid NIRS-EEG brain computer interface. NeuroImage 59(1): 519-529 (2012) - [j95]Felix Bießmann, Yusuke Murayama, Nikos K. Logothetis, Klaus-Robert Müller
Improved decoding of neural activity from fMRI signals using non-separable spatiotemporal deconvolutions. NeuroImage 61(4): 1031-1042 (2012) - [j94]Ning Jiang
Myoelectric Control of Artificial Limbs¿Is There a Need to Change Focus? [In the Spotlight]. IEEE Signal Process. Mag. 29(5): 152-150 (2012) - [j93]Janne Mathias Hahne, Bernhard Graimann, Klaus-Robert Müller
Spatial Filtering for Robust Myoelectric Control. IEEE Trans. Biomed. Eng. 59(5): 1436-1443 (2012) - [j92]Simon Scholler, Sebastian Bosse, Matthias Sebastian Treder, Benjamin Blankertz
Toward a Direct Measure of Video Quality Perception Using EEG. IEEE Trans. Image Process. 21(5): 2619-2629 (2012) - [j91]Duncan A. J. Blythe, Paul von Bünau
Feature Extraction for Change-Point Detection Using Stationary Subspace Analysis. IEEE Trans. Neural Networks Learn. Syst. 23(4): 631-643 (2012) - [c91]Wojciech Samek, Klaus-Robert Müller
Brain-computer interfacing in discriminative and stationary subspaces. EMBC 2012: 2873-2876 - [c90]Javier Pascual, Francisco Velasco-Álvarez
First study towards linear control of an upper-limb neuroprosthesis with an EEG-based Brain-Computer Interface. EMBC 2012: 3269-3273 - [c89]Claudia Sannelli, Carmen Vidaurre
Common Spatial Pattern Patches: Online evaluation on BCI-naive users. EMBC 2012: 4744-4747 - [c88]Franz J. Király, Andreas Ziehe, Klaus-Robert Müller
An Algebraic Method for Approximate Rank One Factorization of Rank Deficient Matrices. LVA/ICA 2012: 272-279 - [c87]Felix Bießmann, Jens-Michalis Papaioannou, Andreas Harth
Quantifying spatiotemporal dynamics of twitter replies to news feeds. MLSP 2012: 1-6 - [c86]Janne Mathias Hahne, Hubertus Rehbaum, Felix Bießmann, Frank C. Meinecke, Klaus-Robert Müller
Simultaneous and proportional control of 2D wrist movements with myoelectric signals. MLSP 2012: 1-6 - [c85]Grégoire Montavon, Katja Hansen, Siamac Fazli, Matthias Rupp, Franziska Biegler, Andreas Ziehe, Alexandre Tkatchenko, O. Anatole von Lilienfeld, Klaus-Robert Müller:
Learning Invariant Representations of Molecules for Atomization Energy Prediction. NIPS 2012: 449-457 - [c84]Franz J. Király, Paul von Bünau, Jan Saputra Müller, Duncan A. J. Blythe, Frank C. Meinecke, Klaus-Robert Müller:
Regression for sets of polynomial equations. AISTATS 2012: 628-637 - [c83]Grégoire Montavon, Mikio L. Braun, Klaus-Robert Müller:
Deep Boltzmann Machines as Feed-Forward Hierarchies. AISTATS 2012: 798-804 - [p19]Klaus-Robert Müller:
Introduction. Neural Networks: Tricks of the Trade (2nd ed.) 2012: 1-5 - [p18]Klaus-Robert Müller:
Speeding Learning. Neural Networks: Tricks of the Trade (2nd ed.) 2012: 7-8 - [p17]Yann LeCun, Léon Bottou, Genevieve B. Orr, Klaus-Robert Müller:
Efficient BackProp. Neural Networks: Tricks of the Trade (2nd ed.) 2012: 9-48 - [p16]Klaus-Robert Müller:
Regularization Techniques to Improve Generalization. Neural Networks: Tricks of the Trade (2nd ed.) 2012: 49-51 - [p15]Klaus-Robert Müller:
Improving Network Models and Algorithmic Tricks. Neural Networks: Tricks of the Trade (2nd ed.) 2012: 139-141 - [p14]Klaus-Robert Müller:
Representing and Incorporating Prior Knowledge in Neural Network Training. Neural Networks: Tricks of the Trade (2nd ed.) 2012: 231-233 - [p13]Klaus-Robert Müller:
Tricks for Time Series. Neural Networks: Tricks of the Trade (2nd ed.) 2012: 339-341 - [p12]Grégoire Montavon, Klaus-Robert Müller:
Big Learning and Deep Neural Networks. Neural Networks: Tricks of the Trade (2nd ed.) 2012: 419-420 - [p11]Grégoire Montavon, Klaus-Robert Müller:
Better Representations: Invariant, Disentangled and Reusable. Neural Networks: Tricks of the Trade (2nd ed.) 2012: 559-560 - [p10]Grégoire Montavon, Klaus-Robert Müller:
Deep Boltzmann Machines and the Centering Trick. Neural Networks: Tricks of the Trade (2nd ed.) 2012: 621-637 - [p9]Grégoire Montavon, Klaus-Robert Müller:
Identifying Dynamical Systems for Forecasting and Control. Neural Networks: Tricks of the Trade (2nd ed.) 2012: 657-658 - [e4]Grégoire Montavon, Genevieve B. Orr, Klaus-Robert Müller
Neural Networks: Tricks of the Trade - Second Edition. Lecture Notes in Computer Science 7700, Springer 2012, ISBN 978-3-642-35288-1 [contents] - [i7]Grégoire Montavon, Klaus-Robert Müller:
Learning Feature Hierarchies with Centered Deep Boltzmann Machines. CoRR abs/1203.3783 (2012) - [i6]Wojciech Samek, Frank C. Meinecke, Klaus-Robert Müller:
Transferring Subspaces Between Subjects in Brain-Computer Interfacing. CoRR abs/1209.4115 (2012) - 2011
- [j90]Fabian Rathke, Katja Hansen, Ulf Brefeld, Klaus-Robert Müller
StructRank: A New Approach for Ligand-Based Virtual Screening. J. Chem. Inf. Model. 51(1): 83-92 (2011) - [j89]Grégoire Montavon, Mikio L. Braun, Klaus-Robert Müller:
Kernel Analysis of Deep Networks. J. Mach. Learn. Res. 12: 2563-2581 (2011) - [j88]Jan Saputra Müller, Paul von Bünau, Frank C. Meinecke, Franz J. Király, Klaus-Robert Müller:
The Stationary Subspace Analysis Toolbox. J. Mach. Learn. Res. 12: 3065-3069 (2011) - [j87]Carmen Vidaurre
Machine-Learning-Based Coadaptive Calibration for Brain-Computer Interfaces. Neural Comput. 23(3): 791-816 (2011) - [j86]Stefan Haufe
Large-scale EEG/MEG source localization with spatial flexibility. NeuroImage 54(2): 851-859 (2011) - [j85]Steven Lemm, Benjamin Blankertz, Thorsten Dickhaus
Introduction to machine learning for brain imaging. NeuroImage 56(2): 387-399 (2011) - [j84]Benjamin Blankertz, Steven Lemm, Matthias Sebastian Treder, Stefan Haufe
Single-trial analysis and classification of ERP components - A tutorial. NeuroImage 56(2): 814-825 (2011) - [j83]Siamac Fazli
ℓ1-penalized linear mixed-effects models for high dimensional data with application to BCI. NeuroImage 56(4): 2100-2108 (2011) - [j82]Carmen Vidaurre
Toward Unsupervised Adaptation of LDA for Brain-Computer Interfaces. IEEE Trans. Biomed. Eng. 58(3): 587-597 (2011) - [j81]Fabian J. Theis
Uniqueness of Non-Gaussianity-Based Dimension Reduction. IEEE Trans. Signal Process. 59(9): 4478-4482 (2011) - [c82]Alexander Binder, Wojciech Samek, Marius Kloft, Christina Müller, Klaus-Robert Müller, Motoaki Kawanabe:
The Joint Submission of the TU Berlin and Fraunhofer FIRST (TUBFI) to the ImageCLEF2011 Photo Annotation Task. CLEF (Notebook Papers/Labs/Workshop) 2011 - [c81]Anne K. Porbadnigk, Simon Scholler, Benjamin Blankertz, Arnd Ritz, Matthias Born, Robert Scholl, Klaus-Robert Müller
Revealing the neural response to imperceptible peripheral flicker with machine learning. EMBC 2011: 3692-3695 - [c80]Siamac Fazli
ℓ1-Penalized Linear Mixed-Effects Models for BCI. ICANN (1) 2011: 26-35 - [c79]Robert Jenssen, Marius Kloft, Sören Sonnenburg, Alexander Zien, Klaus-Robert Müller
A new scatter-based multi-class support vector machine. MLSP 2011: 1-6 - [c78]Felix Bießmann, Yusuke Murayama, Nikos K. Logothetis, Klaus-Robert Müller, Frank C. Meinecke:
Non-separable Spatiotemporal Brain Hemodynamics Contain Neural Information. MLINI 2011: 140-147 - [c77]Stefan Haufe
Pitfalls in EEG-Based Brain Effective Connectivity Analysis. MLINI 2011: 202-209 - [i5]Duncan A. J. Blythe, Paul von Bünau, Frank C. Meinecke, Klaus-Robert Müller:
Feature Extraction for Change-Point Detection using Stationary Subspace Analysis. CoRR abs/1108.2486 (2011) - [i4]Daniel Bartz, Kerr Hatrick, Christian W. Hesse, Klaus-Robert Müller, Steven Lemm:
Directional Variance Adjustment: a novel covariance estimator for high dimensional portfolio optimization. CoRR abs/1109.3069 (2011) - [i3]Alexander Binder, Shinichi Nakajima, Marius Kloft, Christina Müller, Wojciech Samek, Ulf Brefeld, Klaus-Robert Müller, Motoaki Kawanabe:
Insights from Classifying Visual Concepts with Multiple Kernel Learning. CoRR abs/1112.3697 (2011) - [i2]John C. Snyder, Matthias Rupp, Katja Hansen, Klaus-Robert Müller, Kieron Burke:
Finding Density Functionals with Machine Learning. CoRR abs/1112.5441 (2011) - 2010
- [j80]Bastian Venthur, Simon Scholler, John Williamson, Sven Dähne, Matthias Sebastian Treder, Maria T. Kramarek, Klaus-Robert Müller
Pyff - A Pythonic Framework for Feedback Applications and Stimulus Presentation in Neuroscience. Frontiers Neuroinformatics 4: 179 (2010) - [j79]Matthias Rupp, Timon Schroeter, Ramona Steri, Ewgenij Proschak, Katja Hansen, Heiko Zettl, Oliver Rau, Manfred Schubert-Zsilavecz, Klaus-Robert Müller
Kernel learning for ligand-based virtual screening: discovery of a new PPARγ agonist. J. Cheminformatics 2(S-1): 27 (2010) - [j78]Iurii Sushko, Sergii Novotarskyi, Robert Körner, Anil Kumar Pandey, Artem Cherkasov, Jiazhong Li, Paola Gramatica
Applicability Domains for Classification Problems: Benchmarking of Distance to Models for Ames Mutagenicity Set. J. Chem. Inf. Model. 50(12): 2094-2111 (2010) - [j77]Konrad Rieck, Tammo Krueger, Ulf Brefeld, Klaus-Robert Müller:
Approximate Tree Kernels. J. Mach. Learn. Res. 11: 555-580 (2010) - [j76]David Baehrens, Timon Schroeter, Stefan Harmeling, Motoaki Kawanabe, Katja Hansen, Klaus-Robert Müller:
How to Explain Individual Classification Decisions. J. Mach. Learn. Res. 11: 1803-1831 (2010) - [j75]Felix Bießmann, Frank C. Meinecke, Arthur Gretton
Temporal kernel CCA and its application in multimodal neuronal data analysis. Mach. Learn. 79(1-2): 5-27 (2010) - [j74]Ryota Tomioka, Klaus-Robert Müller
A regularized discriminative framework for EEG analysis with application to brain-computer interface. NeuroImage 49(1): 415-432 (2010) - [j73]Benjamin Blankertz, Claudia Sannelli, Sebastian Halder
Neurophysiological predictor of SMR-based BCI performance. NeuroImage 51(4): 1303-1309 (2010) - [j72]Stefan Haufe
Modeling Sparse Connectivity Between Underlying Brain Sources for EEG/MEG. IEEE Trans. Biomed. Eng. 57(8): 1954-1963 (2010) - [c76]Carmen Vidaurre
Machine-Learning Based Co-adaptive Calibration: A Perspective to Fight BCI Illiteracy. HAIS (1) 2010: 413-420 - [c75]Grégoire Montavon, Mikio L. Braun, Klaus-Robert Müller:
Layer-wise analysis of deep networks with Gaussian kernels. NIPS 2010: 1678-1686 - [c74]Stefan Haufe, Klaus-Robert Müller, Guido Nolte, Nicole Krämer:
Sparse Causal Discovery in Multivariate Time Series. NIPS Causality: Objectives and Assessment 2010: 97-106 - [c73]Guido Nolte, Andreas Ziehe, Nicole Krämer, Florin Popescu, Klaus-Robert Müller:
Comparison of Granger Causality and Phase Slope Index. NIPS Causality: Objectives and Assessment 2010: 267-276 - [p8]Siamac Fazli, Márton Danóczy, Florin Popescu, Benjamin Blankertz, Klaus-Robert Müller
Using Rest Class and Control Paradigms for Brain Computer Interfacing. Brain-Computer Interfaces 2010: 55-70
2000 – 2009
- 2009
- [j71]Stefan Wahl, Konrad Rieck, Pavel Laskov, Peter Domschitz, Klaus-Robert Müller
Securing IMS against novel threats. Bell Labs Tech. J. 14(1): 243-257 (2009) - [j70]John Williamson, Roderick Murray-Smith
Designing for uncertain, asymmetric control: Interaction design for brain-computer interfaces. Int. J. Hum. Comput. Stud. 67(10): 827-841 (2009) - [j69]Katja Hansen, Sebastian Mika, Timon Schroeter, Andreas Sutter, Antonius ter Laak
Benchmark Data Set for in Silico Prediction of Ames Mutagenicity. J. Chem. Inf. Model. 49(9): 2077-2081 (2009) - [j68]Tadashi Isa, Eberhard E. Fetz, Klaus-Robert Müller
Recent advances in brain-machine interfaces. Neural Networks 22(9): 1201-1202 (2009) - [j67]Claudia Sannelli, Mikio L. Braun, Klaus-Robert Müller
Improving BCI performance by task-related trial pruning. Neural Networks 22(9): 1295-1304 (2009) - [j66]Siamac Fazli
Subject-independent mental state classification in single trials. Neural Networks 22(9): 1305-1312 (2009) - [j65]Steven Lemm, Klaus-Robert Müller
A Generalized Framework for Quantifying the Dynamics of EEG Event-Related Desynchronization. PLoS Comput. Biol. 5(8) (2009) - [c72]Frank C. Meinecke, Paul von Bünau, Motoaki Kawanabe, Klaus-Robert Müller:
Learning invariances with Stationary Subspace Analysis. ICCV Workshops 2009: 87-92 - [c71]Paul von Bünau, Frank C. Meinecke, Klaus-Robert Müller
Stationary Subspace Analysis. ICA 2009: 1-8 - [c70]Siamac Fazli
Using Rest Class and Control Paradigms for Brain Computer Interfacing. IWANN (1) 2009: 651-665 - [c69]Motoaki Kawanabe, Carmen Vidaurre
A Maxmin Approach to Optimize Spatial Filters for EEG Single-Trial Classification. IWANN (1) 2009: 674-682 - [c68]Siamac Fazli, Cristian Grozea, Márton Danóczy, Benjamin Blankertz, Florin Popescu, Klaus-Robert Müller:
Subject independent EEG-based BCI decoding. NIPS 2009: 513-521 - [c67]Marius Kloft, Ulf Brefeld, Sören Sonnenburg, Pavel Laskov, Klaus-Robert Müller, Alexander Zien:
Efficient and Accurate Lp-Norm Multiple Kernel Learning. NIPS 2009: 997-1005 - [i1]David Baehrens, Timon Schroeter, Stefan Harmeling, Motoaki Kawanabe, Katja Hansen, Klaus-Robert Müller:
How to Explain Individual Classification Decisions. CoRR abs/0912.1128 (2009) - 2008
- [j64]Anton Nijholt
Brain-Computer Interfacing for Intelligent Systems. IEEE Intell. Syst. 23(3): 72-79 (2008) - [j63]Masashi Sugiyama, Motoaki Kawanabe, Gilles Blanchard, Klaus-Robert Müller
Approximating the Best Linear Unbiased Estimator of Non-Gaussian Signals with Gaussian Noise. IEICE Trans. Inf. Syst. 91-D(5): 1577-1580 (2008) - [j62]Anton Schwaighofer, Timon Schroeter, Sebastian Mika, Katja Hansen, Antonius ter Laak
A Probabilistic Approach to Classifying Metabolic Stability. J. Chem. Inf. Model. 48(4): 785-796 (2008) - [j61]Mikio L. Braun, Joachim M. Buhmann, Klaus-Robert Müller:
On Relevant Dimensions in Kernel Feature Spaces. J. Mach. Learn. Res. 9: 1875-1908 (2008) - [j60]Stefan Haufe
Combining sparsity and rotational invariance in EEG/MEG source reconstruction. NeuroImage 42(2): 726-738 (2008) - [j59]Paul Sajda, Klaus-Robert Müller
Brain-Computer Interfaces [from the guest editors]. IEEE Signal Process. Mag. 25(1): 16-17 (2008) - [j58]Benjamin Blankertz, Ryota Tomioka, Steven Lemm, Motoaki Kawanabe, Klaus-Robert Müller
Optimizing Spatial filters for Robust EEG Single-Trial Analysis. IEEE Signal Process. Mag. 25(1): 41-56 (2008) - [j57]Benjamin Blankertz, Florian Losch, Matthias Krauledat, Guido Dornhege, Gabriel Curio
The Berlin Brain-Computer Interface: Accurate Performance From First-Session in BCI-NaÏve Subjects. IEEE Trans. Biomed. Eng. 55(10): 2452-2462 (2008) - [c66]Vojtech Franc, Pavel Laskov, Klaus-Robert Müller
Stopping conditions for exact computation of leave-one-out error in support vector machines. ICML 2008: 328-335 - [c65]Konrad Rieck, Stefan Wahl, Pavel Laskov, Peter Domschitz, Klaus-Robert Müller
A Self-learning System for Detection of Anomalous SIP Messages. IPTComm 2008: 90-106 - [c64]Stefan Haufe, Vadim V. Nikulin, Andreas Ziehe, Klaus-Robert Müller, Guido Nolte:
Estimating vector fields using sparse basis field expansions. NIPS 2008: 617-624 - [c63]Michael Tangermann, Matthias Krauledat, Konrad Grzeska, Max Sagebaum, Benjamin Blankertz, Carmen Vidaurre, Klaus-Robert Müller:
Playing Pinball with non-invasive BCI. NIPS 2008: 1641-1648 - [c62]Benjamin Blankertz, Michael Tangermann
The Berlin Brain-Computer Interface. WCCI 2008: 79-101 - 2007
- [j56]Roman Krepki, Gabriel Curio
Berlin Brain-Computer Interface - The HCI communication channel for discovery. Int. J. Hum. Comput. Stud. 65(5): 460-477 (2007) - [j55]Timon Schroeter, Anton Schwaighofer, Sebastian Mika, Antonius ter Laak
Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules. J. Comput. Aided Mol. Des. 21(9): 485-498 (2007) - [j54]Timon Schroeter, Anton Schwaighofer, Sebastian Mika, Antonius ter Laak
Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules. J. Comput. Aided Mol. Des. 21(12): 651-664 (2007) - [j53]Anton Schwaighofer, Timon Schroeter, Sebastian Mika, Julian Laub, Antonius ter Laak
Accurate Solubility Prediction with Error Bars for Electrolytes: A Machine Learning Approach. J. Chem. Inf. Model. 47(2): 407-424 (2007) - [j52]Masashi Sugiyama, Matthias Krauledat, Klaus-Robert Müller:
Covariate Shift Adaptation by Importance Weighted Cross Validation. J. Mach. Learn. Res. 8: 985-1005 (2007) - [j51]Sören Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Léon Bottou, Geoffrey Holmes, Yann LeCun, Klaus-Robert Müller, Fernando Pereira, Carl Edward Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Alexander J. Smola, Pascal Vincent, Jason Weston, Robert C. Williamson:
The Need for Open Source Software in Machine Learning. J. Mach. Learn. Res. 8: 2443-2466 (2007) - [j50]Gilles Blanchard, Christin Schäfer, Yves Rozenholc
Optimal dyadic decision trees. Mach. Learn. 66(2-3): 209-241 (2007) - [j49]Roman Krepki, Benjamin Blankertz, Gabriel Curio
The Berlin Brain-Computer Interface (BBCI) - towards a new communication channel for online control in gaming applications. Multim. Tools Appl. 33(1): 73-90 (2007) - [j48]Benjamin Blankertz, Guido Dornhege, Matthias Krauledat, Klaus-Robert Müller
The non-invasive Berlin Brain-Computer Interface: Fast acquisition of effective performance in untrained subjects. NeuroImage 37(2): 539-550 (2007) - [j47]Gunnar Rätsch
Improving the Caenorhabditis elegans Genome Annotation Using Machine Learning. PLoS Comput. Biol. 3(2) (2007) - [c61]Klaus-Robert Müller
Machine Learning and Applications for Brain-Computer Interfacing. HCI (8) 2007: 705-714 - [c60]Benjamin Blankertz, Matthias Krauledat, Guido Dornhege, John Williamson, Roderick Murray-Smith, Klaus-Robert Müller
A Note on Brain Actuated Spelling with the Berlin Brain-Computer Interface. HCI (6) 2007: 759-768 - [c59]Keisuke Yamazaki, Motoaki Kawanabe, Sumio Watanabe, Masashi Sugiyama, Klaus-Robert Müller
Asymptotic Bayesian generalization error when training and test distributions are different. ICML 2007: 1079-1086 - [c58]Pavel Laskov, Konrad Rieck, Klaus-Robert Müller:
Machine Learning for Intrusion Detection. NATO ASI Mining Massive Data Sets for Security 2007: 366-373 - [c57]Benjamin Blankertz, Motoaki Kawanabe, Ryota Tomioka, Friederike U. Hohlefeld, Vadim V. Nikulin, Klaus-Robert Müller:
Invariant Common Spatial Patterns: Alleviating Nonstationarities in Brain-Computer Interfacing. NIPS 2007: 113-120 - [c56]Shigeyuki Oba, Motoaki Kawanabe, Klaus-Robert Müller, Shin Ishii:
Heterogeneous Component Analysis. NIPS 2007: 1097-1104 - 2006
- [j46]Stefan Harmeling, Guido Dornhege, David M. J. Tax, Frank C. Meinecke, Klaus-Robert Müller
From outliers to prototypes: Ordering data. Neurocomputing 69(13-15): 1608-1618 (2006) - [j45]Gilles Blanchard, Motoaki Kawanabe, Masashi Sugiyama, Vladimir G. Spokoiny, Klaus-Robert Müller:
In Search of Non-Gaussian Components of a High-Dimensional Distribution. J. Mach. Learn. Res. 7: 247-282 (2006) - [j44]Pavel Laskov, Christian Gehl, Stefan Krüger, Klaus-Robert Müller:
Incremental Support Vector Learning: Analysis, Implementation and Applications. J. Mach. Learn. Res. 7: 1909-1936 (2006) - [j43]Benjamin Blankertz
The Berlin Brain-Computer Interface: Machine Learning Based Detection of User Specific Brain States. J. Univers. Comput. Sci. 12(6): 581-607 (2006) - [j42]Klaus-Robert Müller:
Das Berliner Brain-Computer Interface. Künstliche Intell. 20(4): 60-61 (2006) - [j41]Julian Laub, Volker Roth
On the information and representation of non-Euclidean pairwise data. Pattern Recognit. 39(10): 1815-1826 (2006) - [j40]Klaus-Robert Müller
Toward noninvasive brain-computer interfaces. IEEE Signal Process. Mag. 23(5): 128-126 (2006) - [j39]Steven Lemm, Gabriel Curio
Enhancing the signal-to-noise ratio of ICA-based extracted ERPs. IEEE Trans. Biomed. Eng. 53(4): 601-607 (2006) - [j38]Guido Dornhege, Benjamin Blankertz, Matthias Krauledat, Florian Losch, Gabriel Curio
Combined Optimization of Spatial and Temporal Filters for Improving Brain-Computer Interfacing. IEEE Trans. Biomed. Eng. 53(11): 2274-2281 (2006) - [c55]Masashi Sugiyama, Benjamin Blankertz, Matthias Krauledat, Guido Dornhege, Klaus-Robert Müller
Importance-Weighted Cross-Validation for Covariate Shift. DAGM-Symposium 2006: 354-363 - [c54]Konrad Rieck, Pavel Laskov, Klaus-Robert Müller
Efficient Algorithms for Similarity Measures over Sequential Data: A Look Beyond Kernels. DAGM-Symposium 2006: 374-383 - [c53]Ryota Tomioka, Guido Dornhege, Guido Nolte, Kazuyuki Aihara, Klaus-Robert Müller
Optimizing Spectral Filters for Single Trial EEG Classification. DAGM-Symposium 2006: 414-423 - [c52]Klaus-Robert Müller:
Algorithms for on-line differentiation of neuroelectric activities. EMBC (Supplement) 2006: 6525 - [c51]Matthias Krauledat, Benjamin Blankertz, Guido Dornhege, Michael Tangermann, Gabriel Curio
On-line Differentiation Of Neuroelectric Activities: Algorithms And applications. EMBC (Supplement) 2006: 6715-6719 - [c50]Motoaki Kawanabe, Gilles Blanchard, Masashi Sugiyama, Vladimir G. Spokoiny, Klaus-Robert Müller
A Novel Dimension Reduction Procedure for Searching Non-Gaussian Subspaces. ICA 2006: 149-156 - [c49]Keisuke Yamazaki, Kenji Nagata, Sumio Watanabe, Klaus-Robert Müller
A Model Selection Method Based on Bound of Learning Coefficient. ICANN (2) 2006: 371-380 - [c48]Masashi Sugiyama, Motoaki Kawanabe, Gilles Blanchard, Vladimir G. Spokoiny, Klaus-Robert Müller
Obtaining the Best Linear Unbiased Estimator of Noisy Signals by Non-Gaussian Component Analysis. ICASSP (3) 2006: 608-611 - [c47]Mikio L. Braun, Joachim M. Buhmann, Klaus-Robert Müller:
Denoising and Dimension Reduction in Feature Space. NIPS 2006: 185-192 - [c46]Matthias Krauledat, Michael Schröder, Benjamin Blankertz, Klaus-Robert Müller:
Reducing Calibration Time For Brain-Computer Interfaces: A Clustering Approach. NIPS 2006: 753-760 - [c45]Julian Laub, Jakob H. Macke, Klaus-Robert Müller, Felix A. Wichmann:
Inducing Metric Violations in Human Similarity Judgements. NIPS 2006: 777-784 - [c44]Ryota Tomioka, Kazuyuki Aihara, Klaus-Robert Müller:
Logistic Regression for Single Trial EEG Classification. NIPS 2006: 1377-1384 - [e3]Katrin Franke, Klaus-Robert Müller
Pattern Recognition, 28th DAGM Symposium, Berlin, Germany, September 12-14, 2006, Proceedings. Lecture Notes in Computer Science 4174, Springer 2006, ISBN 3-540-44412-2 [contents] - 2005
- [j37]Frank C. Meinecke, Stefan Harmeling, Klaus-Robert Müller
Inlier-based ICA with an application to superimposed images. Int. J. Imaging Syst. Technol. 15(1): 48-55 (2005) - [j36]Klaus-Robert Müller
Classifying 'Drug-likeness' with Kernel-Based Learning Methods. J. Chem. Inf. Model. 45(2): 249-253 (2005) - [j35]Motoaki Kawanabe, Klaus-Robert Müller:
Estimating Functions for Blind Separation When Sources Have Variance Dependencies. J. Mach. Learn. Res. 6: 453-482 (2005) - [j34]Steven Lemm, Benjamin Blankertz, Gabriel Curio
Spatio-spectral filters for improving the classification of single trial EEG. IEEE Trans. Biomed. Eng. 52(9): 1541-1548 (2005) - [c43]Masashi Sugiyama, Klaus-Robert Müller
Model Selection Under Covariate Shift. ICANN (2) 2005: 235-240 - [c42]Gilles Blanchard, Masashi Sugiyama, Motoaki Kawanabe, Vladimir G. Spokoiny, Klaus-Robert Müller:
Non-Gaussian Component Analysis: a Semi-parametric Framework for Linear Dimension Reduction. NIPS 2005: 131-138 - [c41]Guido Dornhege, Benjamin Blankertz, Matthias Krauledat, Florian Losch, Gabriel Curio, Klaus-Robert Müller:
Optimizing spatio-temporal filters for improving Brain-Computer Interfacing. NIPS 2005: 315-322 - [c40]Guido Nolte, Andreas Ziehe, Frank C. Meinecke, Klaus-Robert Müller:
Analyzing Coupled Brain Sources: Distinguishing True from Spurious Interaction. NIPS 2005: 1027-1034 - [c39]Pavel Laskov, Konrad Rieck, Christin Schäfer, Klaus-Robert Müller:
Visualization of anomaly detection using prediction sensitivity. Sicherheit 2005: 197-208 - 2004
- [j33]Klaus-Robert Müller
Blind Source Separation Techniques for Decomposing Event-Related Brain Signals. Int. J. Bifurc. Chaos 14(2): 773-791 (2004) - [j32]Andreas Ziehe, Pavel Laskov, Guido Nolte, Klaus-Robert Müller:
A Fast Algorithm for Joint Diagonalization with Non-orthogonal Transformations and its Application to Blind Source Separation. J. Mach. Learn. Res. 5: 777-800 (2004) - [j31]Julian Laub, Klaus-Robert Müller:
Feature Discovery in Non-Metric Pairwise Data. J. Mach. Learn. Res. 5: 801-818 (2004) - [j30]Koji Tsuda, Shotaro Akaho
Asymptotic Properties of the Fisher Kernel. Neural Comput. 16(1): 115-137 (2004) - [j29]Masashi Sugiyama, Motoaki Kawanabe, Klaus-Robert Müller
Trading Variance Reduction with Unbiasedness: The Regularized Subspace Information Criterion for Robust Model Selection in Kernel Regression. Neural Comput. 16(5): 1077-1104 (2004) - [j28]Pavel Laskov, Christin Schäfer, Igor V. Kotenko, Klaus-Robert Müller
Intrusion Detection in Unlabeled Data with Quarter-sphere Support Vector Machines. Prax. Inf.verarb. Kommun. 27(4): 228-236 (2004) - [j27]Stefan Harmeling, Frank C. Meinecke, Klaus-Robert Müller
Injecting noise for analysing the stability of ICA components. Signal Process. 84(2): 255-266 (2004) - [j26]Miguel A. L. Nicolelis, Niels Birbaumer, Klaus-Robert Müller
Editorial. IEEE Trans. Biomed. Eng. 51(6): 877-880 (2004) - [j25]Guido Dornhege, Benjamin Blankertz, Gabriel Curio
Boosting bit rates in noninvasive EEG single-trial classifications by feature combination and multiclass paradigms. IEEE Trans. Biomed. Eng. 51(6): 993-1002 (2004) - [j24]Benjamin Blankertz, Klaus-Robert Müller
The BCI competition 2003: progress and perspectives in detection and discrimination of EEG single trials. IEEE Trans. Biomed. Eng. 51(6): 1044-1051 (2004) - [c38]Masashi Sugiyama, Motoaki Kawanabe, Klaus-Robert Müller:
Regularizing generalization error estimators: a novel approach to robust model selection. ESANN 2004: 163-168 - [c37]Arie Yeredor, Andreas Ziehe, Klaus-Robert Müller
Approximate Joint Diagonalization Using a Natural Gradient Approach. ICA 2004: 89-96 - [c36]Motoaki Kawanabe, Klaus-Robert Müller
Estimating Functions for Blind Separation when Sources Have Variance-Dependencies. ICA 2004: 136-143 - [c35]Frank C. Meinecke, Stefan Harmeling, Klaus-Robert Müller
Robust ICA for Super-Gaussian Sources. ICA 2004: 217-224 - [c34]David M. J. Tax, Klaus-Robert Müller
A Consistency-Based Model Selection for One-Class Classification. ICPR (3) 2004: 363-366 - 2003
- [j23]Andreas Ziehe, Motoaki Kawanabe, Stefan Harmeling, Klaus-Robert Müller:
Blind Separation of Post-nonlinear Mixtures using Linearizing Transformations and Temporal Decorrelation. J. Mach. Learn. Res. 4: 1319-1338 (2003) - [j22]Stefan Harmeling, Andreas Ziehe, Motoaki Kawanabe, Klaus-Robert Müller
Kernel-Based Nonlinear Blind Source Separation. Neural Comput. 15(5): 1089-1124 (2003) - [j21]Sebastian Mika, Gunnar Rätsch
Constructing Descriptive and Discriminative Nonlinear Features: Rayleigh Coefficients in Kernel Feature Spaces. IEEE Trans. Pattern Anal. Mach. Intell. 25(5): 623-633 (2003) - [c33]David M. J. Tax, Klaus-Robert Müller
Feature Extraction for One-Class Classification. ICANN 2003: 342-349 - [c32]Guido Dornhege, Benjamin Blankertz, Gabriel Curio, Klaus-Robert Müller:
Increase Information Transfer Rates in BCI by CSP Extension to Multi-class. NIPS 2003: 733-740 - 2002
- [j20]Masashi Sugiyama, Klaus-Robert Müller:
The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces. J. Mach. Learn. Res. 3: 323-359 (2002) - [j19]Koji Tsuda, Motoaki Kawanabe, Gunnar Rätsch
A New Discriminative Kernel from Probabilistic Models. Neural Comput. 14(10): 2397-2414 (2002) - [j18]Noboru Murata
On-line learning in changing environments with applications in supervised and unsupervised learning. Neural Networks 15(4-6): 743-760 (2002) - [j17]Gunnar Rätsch
Constructing Boosting Algorithms from SVMs: An Application to One-Class Classification. IEEE Trans. Pattern Anal. Mach. Intell. 24(9): 1184-1199 (2002) - [j16]Frank C. Meinecke, Andreas Ziehe, Motoaki Kawanabe, Klaus-Robert Müller
A resampling approach to estimate the stability of one-dimensional or multidimensional independent components. IEEE Trans. Biomed. Eng. 49(12): 1514-1525 (2002) - [j15]Koji Tsuda, Masashi Sugiyama, Klaus-Robert Müller
Subspace information criterion for nonquadratic regularizers-Model selection for sparse regressors. IEEE Trans. Neural Networks 13(1): 70-80 (2002) - [c31]Sören Sonnenburg, Gunnar Rätsch
New Methods for Splice Site Recognition. ICANN 2002: 329-336 - [c30]Masashi Sugiyama, Klaus-Robert Müller
Selecting Ridge Parameters in Infinite Dimensional Hypothesis Spaces. ICANN 2002: 528-534 - [c29]Koji Tsuda, Motoaki Kawanabe, Klaus-Robert Müller:
Clustering with the Fisher Score. NIPS 2002: 729-736 - [c28]Volker Roth, Julian Laub, Joachim M. Buhmann, Klaus-Robert Müller:
Going Metric: Denoising Pairwise Data. NIPS 2002: 817-824 - [c27]Guido Dornhege, Benjamin Blankertz, Gabriel Curio, Klaus-Robert Müller:
Combining Features for BCI. NIPS 2002: 1115-1122 - 2001
- [j14]Gunnar Rätsch
Soft Margins for AdaBoost. Mach. Learn. 42(3): 287-320 (2001) - [j13]Klaus-Robert Müller
An introduction to kernel-based learning algorithms. IEEE Trans. Neural Networks 12(2): 181-201 (2001) - [c26]Koji Tsuda, Gunnar Rätsch
Learning to Predict the Leave-One-Out Error of Kernel Based Classifiers. ICANN 2001: 331-338 - [c25]Benjamin Blankertz, Gabriel Curio, Klaus-Robert Müller:
Classifying Single Trial EEG: Towards Brain Computer Interfacing. NIPS 2001: 157-164 - [c24]Stefan Harmeling, Andreas Ziehe, Motoaki Kawanabe, Klaus-Robert Müller:
Kernel Feature Spaces and Nonlinear Blind Souce Separation. NIPS 2001: 761-768 - [c23]Koji Tsuda, Motoaki Kawanabe, Gunnar Rätsch, Sören Sonnenburg, Klaus-Robert Müller:
A New Discriminative Kernel From Probabilistic Models. NIPS 2001: 977-984 - [c22]Frank C. Meinecke, Andreas Ziehe, Motoaki Kawanabe, Klaus-Robert Müller:
Estimating the Reliability of ICA Projections. NIPS 2001: 1181-1188 - 2000
- [j12]Jens Kohlmorgen, Klaus-Robert Müller
Identification of nonstationary dynamics in physiological recordings. Biol. Cybern. 83(1): 73-84 (2000) - [j11]Alexander Zien, Gunnar Rätsch
Engineering support vector machine kernels that recognize translation initiation sites. Bioinform. 16(9): 799-807 (2000) - [j10]Andreas Ziehe, Klaus-Robert Müller
Artifact reduction in magnetoneurography based on time-delayed second-order correlations. IEEE Trans. Biomed. Eng. 47(1): 75-87 (2000) - [j9]Gerd Wübbeler, Andreas Ziehe, Bruno-Marcel Mackert, Klaus-Robert Müller
Independent component analysis of noninvasively recorded cortical magnetic DC-fields in humans. IEEE Trans. Biomed. Eng. 47(5): 594-599 (2000) - [c21]Gunnar Rätsch, Manfred K. Warmuth, Sebastian Mika, Takashi Onoda, Steven Lemm, Klaus-Robert Müller:
Barrier Boosting. COLT 2000: 170-179 - [c20]Sebastian Mika, Gunnar Rätsch, Klaus-Robert Müller:
A Mathematical Programming Approach to the Kernel Fisher Algorithm. NIPS 2000: 591-597 - [c19]Gunnar Rätsch
Robust Ensemble Learning for Data Mining. PAKDD 2000: 341-344 - [e2]Sara A. Solla, Todd K. Leen, Klaus-Robert Müller:
Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29 - December 4, 1999]. The MIT Press 2000, ISBN 0-262-19450-3 [contents]
1990 – 1999
- 1999
- [j8]Bernhard Schölkopf, Klaus-Robert Müller
Lernen mit Kernen: Support-Vektor-Methoden zur Analyse hochdimensionaler Daten. Inform. Forsch. Entwickl. 14(3): 154-163 (1999) - [j7]Bernhard Schölkopf, Sebastian Mika, Christopher J. C. Burges, Phil Knirsch, Klaus-Robert Müller
Input space versus feature space in kernel-based methods. IEEE Trans. Neural Networks 10(5): 1000-1017 (1999) - [c18]Stefan Liehr, Klaus Pawelzik, Jens Kohlmorgen, Steven Lemm, Klaus-Robert Müller:
Hidden Markov gating for prediction of change points in switching dynamical systems. ESANN 1999: 405-410 - [c17]Alexander Zien, Gunnar Rätsch, Sebastian Mika, Bernhard Schölkopf, Christian Lemmen, Alexander J. Smola, Thomas Lengauer, Klaus-Robert Müller:
Engineering Support Vector Machine Kerneis That Recognize Translation Initialion Sites. German Conference on Bioinformatics 1999: 37-43 - [c16]Ernst A. Hartmann, Dirk Sistenich, Klaus-Robert Müller, Michael Gerads, Holger Sickel:
Tools for computer-supported learning in organisations. HCI (2) 1999: 377-381 - [c15]Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alexander J. Smola, Klaus-Robert Müller:
Invariant Feature Extraction and Classification in Kernel Spaces. NIPS 1999: 526-532 - [c14]Gunnar Rätsch, Bernhard Schölkopf, Alexander J. Smola, Klaus-Robert Müller, Takashi Onoda, Sebastian Mika:
v-Arc: Ensemble Learning in the Presence of Outliers. NIPS 1999: 561-567 - [c13]Lucas C. Parra, Clay Spence, Paul Sajda, Andreas Ziehe, Klaus-Robert Müller:
Unmixing Hyperspectral Data. NIPS 1999: 942-948 - 1998
- [j6]Bernhard Schölkopf, Alexander J. Smola, Klaus-Robert Müller
Nonlinear Component Analysis as a Kernel Eigenvalue Problem. Neural Comput. 10(5): 1299-1319 (1998) - [j5]Alexander J. Smola, Bernhard Schölkopf, Klaus-Robert Müller
The connection between regularization operators and support vector kernels. Neural Networks 11(4): 637-649 (1998) - [j4]Jens Kohlmorgen, Klaus-Robert Müller
Data Set A is a Pattern Matching Problem. Neural Process. Lett. 7(1): 43-47 (1998) - [c12]Gunnar Rätsch, Takashi Onoda, Klaus-Robert Müller:
An Improvement of AdaBoost to Avoid Overfitting. ICONIP 1998: 506-509 - [c11]Sebastian Mika, Bernhard Schölkopf, Alexander J. Smola, Klaus-Robert Müller, Matthias Scholz, Gunnar Rätsch:
Kernel PCA and De-Noising in Feature Spaces. NIPS 1998: 536-542 - [c10]Gunnar Rätsch, Takashi Onoda, Klaus-Robert Müller:
Regularizing AdaBoost. NIPS 1998: 564-570 - [e1]Genevieve B. Orr, Klaus-Robert Müller
Neural Networks: Tricks of the Trade. Lecture Notes in Computer Science 1524, Springer 1998, ISBN 3-540-65311-2 [contents] - 1997
- [j3]Shun-ichi Amari, Noboru Murata
Asymptotic statistical theory of overtraining and cross-validation. IEEE Trans. Neural Networks 8(5): 985-996 (1997) - [c9]Bernhard Schölkopf, Alexander J. Smola, Klaus-Robert Müller
Kernel Principal Component Analysis. ICANN 1997: 583-588 - [c8]Klaus-Robert Müller
Predicting Time Series with Support Vector Machines. ICANN 1997: 999-1004 - [c7]Jens Kohlmorgen, Klaus-Robert Müller
Analysis of Wake/Sleep EEG with Competing Experts. ICANN 1997: 1077-1082 - [c6]Jens Kohlmorgen, Klaus-Robert Müller, Klaus Pawelzik:
Analysis of Drifting Dynamics with Neural Network Hidden Markov Models. NIPS 1997: 735-741 - 1996
- [j2]Klaus Pawelzik, Jens Kohlmorgen, Klaus-Robert Müller
Annealed Competition of Experts for a Segmentation and Classification of Switching Dynamics. Neural Comput. 8(2): 340-356 (1996) - [j1]Klaus-Robert Müller
A Numerical Study on Learning Curves in Stochastic Multilayer Feedforward Networks. Neural Comput. 8(5): 1085-1106 (1996) - [c5]Klaus Pawelzik, Klaus-Robert Müller, Jens Kohlmorgen:
Prediction of Mixtures. ICANN 1996: 127-132 - [c4]Jens Kohlmorgen, Klaus-Robert Müller
Analysis of Drifting Dynamics with Competing Predictors. ICANN 1996: 785-790 - [c3]Noboru Murata, Klaus-Robert Müller, Andreas Ziehe, Shun-ichi Amari:
Adaptive On-line Learning in Changing Environments. NIPS 1996: 599-605 - [p7]Genevieve B. Orr, Klaus-Robert Müller:
Introduction. Neural Networks: Tricks of the Trade 1996: 1-5 - [p6]Genevieve B. Orr, Klaus-Robert Müller:
Speeding Learning: Preface. Neural Networks: Tricks of the Trade 1996: 7-8 - [p5]Yann LeCun, Léon Bottou, Genevieve B. Orr, Klaus-Robert Müller
Effiicient BackProp. Neural Networks: Tricks of the Trade 1996: 9-50 - [p4]Genevieve B. Orr, Klaus-Robert Müller:
Regularization Techniques to Improve Generalization: Preface. Neural Networks: Tricks of the Trade 1996: 51-54 - [p3]Genevieve B. Orr, Klaus-Robert Müller:
Improving Network Models and Algorithmic Tricks: Preface. Neural Networks: Tricks of the Trade 1996: 141-144 - [p2]Genevieve B. Orr, Klaus-Robert Müller:
Representing and Incorporating Prior Knowledge in Neural Network Training: Preface. Neural Networks: Tricks of the Trade 1996: 235-238 - [p1]Genevieve B. Orr, Klaus-Robert Müller:
Tricks for Time Series: Preface. Neural Networks: Tricks of the Trade 1996: 343-346 - 1995
- [c2]Shun-ichi Amari, Noboru Murata, Klaus-Robert Müller, Michael Finke, Howard Hua Yang:
Statistical Theory of Overtraining - Is Cross-Validation Asymptotically Effective? NIPS 1995: 176-182 - 1994
- [b1]Klaus-Robert Müller:
Spärlich verbundene neuronale Netze und ihre Anwendung. Karlsruhe Institute of Technology, Germany, Oldenbourg 1994, ISBN 978-3-486-22837-3, pp. 1-141 - 1993
- [c1]Klaus-Robert Müller
Associative storage and retrieval of highly correlated natural pattern sets in diluted Hopfield networks. ICNN 1993: 889-894
Coauthor Index
[j135] [c154] [c143] [j123] [j122] [j121] [c103] [c99] [c98] [c97] [c96] [j96] [j92] [c89] [j87] [j86] [j85] [j84] [j82] [c81] [j80] [j73] [c76] [p8] [j70] [j66] [c70] [c69] [c68] [j64] [j58] [j57] [c63] [c62] [j56] [j49] [j48] [c61] [c60] [c57] [j43] [j40] [j38] [c55] [c51] [c46] [j34] [c41] [j25] [j24] [c32] [c27] [c25]
Mikio L. Braun
aka: Mikio Ludwig Braun
aka: Mikio Ludwig Braun
Sebastian Lapuschkin
aka: Sebastian Bach
aka: Sebastian Bach
[j192] [j188] [j186] [d3] [d2] [i135] [i131] [i128] [i127] [j183] [c186] [c184] [i121] [i117] [j178] [j172] [j171] [j168] [c180] [c179] [i113] [i105] [i103] [j161] [j160] [i99] [i91] [j153] [c168] [i87] [i86] [i82] [i80] [i76] [j144] [p25] [p24] [p23] [e5] [i73] [i66] [i61] [j138] [i55] [i49] [i47] [i45] [j129] [j125] [c135] [i37] [i36] [i35] [i34] [j124] [c133] [c132] [c130] [c128] [c125] [i27] [i25] [i24] [i17] [i15] [i13] [i12] [i11] [i10] [j102] [c85] [c83] [p12] [p11] [p10] [p9] [e4] [i7] [j89] [c75]
Anne Porbadnigk
aka: Anne K. Porbadnigk
aka: Anne K. Porbadnigk
[j191] [j186] [i128] [j185] [j179] [c186] [j177] [j173] [j168] [c181] [e6] [i105] [j162] [j161] [j160] [j158] [j157] [i98] [i97] [i94] [i91] [j154] [j150] [j148] [c174] [c172] [c169] [c168] [i86] [i84] [i77] [i76] [j145] [j144] [c163] [c162] [c161] [c160] [c159] [c158] [p26] [p25] [p24] [p23] [e5] [i73] [i71] [i70] [i69] [i68] [i66] [i64] [i63] [i62] [i61] [i60] [i59] [i57] [i56] [j138] [j137] [j135] [j134] [i54] [i53] [i51] [i49] [i46] [i45] [i44] [i43] [i41] [j129] [j125] [c146] [c141] [c140] [c135] [i37] [i36] [i35] [i34] [i32] [i31] [j124] [j121] [c133] [c132] [c130] [c129] [c127] [c125] [c124] [c123] [i28] [i27] [i26] [i25] [i24] [i23] [i20] [i17] [i16] [i15] [j115] [j113] [c122] [c119] [c117] [c115] [i12] [i11] [i10] [j112] [c106] [p20] [j106] [j101] [c94] [c93] [c91] [i6] [c82] [i3]
Kristof Schütt
aka: Kristof T. Schütt
aka: Kristof T. Schütt
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