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Marco F. Huber
Person information
- affiliation: University of Stuttgart, Institute of Industrial Manufacturing and Management (IFF), Germany
- affiliation: Fraunhofer Institute for Manufacturing Engineering and Automation (IPA), Stuttgart, Germany
- affiliation (former): USU Software AG, Karlsruhe, Germany
- affiliation (former, PhD 2015): Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
- affiliation (former): AGT International, Darmstadt, Germany
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2020 – today
- 2024
- [j18]Kirolos Abdou
, Osama Mohammed, George Eskandar, Amgad Ibrahim, Paul-Amaury Matt, Marco F. Huber:
Smart nesting: estimating geometrical compatibility in the nesting problem using graph neural networks. J. Intell. Manuf. 35(6): 2811-2827 (2024) - [j17]Florenz Graf
HIPer: A Human-Inspired Scene Perception Model for Multifunctional Mobile Robots. IEEE Trans. Robotics 40: 4668-4683 (2024) - [c96]Xinyang Wu, Elisabeth Wedernikow, Marco F. Huber:
Data-Efficient Uncertainty-Guided Model-Based Reinforcement Learning with Unscented Kalman Bayesian Neural Networks. ACC 2024: 104-110 - [c95]Maximilian-Peter Radtke, Marco F. Huber, Jürgen Bock:
Encoding Machine Phase Information into Heterogeneous Graphs for Adaptive Fault Diagnosis. ETFA 2024: 1-8 - [c94]Max-Lion Schumacher, Marco F. Huber:
Probabilistic Global Robustness Verification of Arbitrary Supervised Machine Learning Models. FUSION 2024: 1-8 - [c93]Markus Walker, Hayk Amirkhanian, Marco F. Huber, Uwe D. Hanebeck:
Trustworthy Bayesian Perceptrons. FUSION 2024: 1-8 - [c92]Jingyi Yu, Tim Pychynski, Karim Said Barsim, Marco F. Huber:
Causal Knowledge in Data Fusion: Systematic Evaluation on Quality Prediction and Root Cause Analysis. FUSION 2024: 1-8 - [c91]Benjamin Alt, Florian Stöckl, Silvan Müller, Christopher Braun, Julian Raible, Saad Alhasan, Oliver Rettig, Lukas Ringle, Darko Katic, Rainer Jäkel, Michael Beetz, Marcus Strand, Marco F. Huber:
RoboGrind: Intuitive and Interactive Surface Treatment with Industrial Robots. ICRA 2024: 2140-2146 - [c90]Tobias Nagel, Marco F. Huber:
Identifying Ordinary Differential Equations for Data-efficient Model-based Reinforcement Learning. IJCNN 2024: 1-10 - [c89]Jingyi Yu, Tim Pychynski, Marco F. Huber:
Causal Knowledge in Data Fusion Subject to Latent Confounding and Measurement Error. MFI 2024: 1-8 - [c88]Patrick Takenaka
ViPro: Enabling and Controlling Video Prediction for Complex Dynamical Scenarios Using Procedural Knowledge. NeSy (1) 2024: 62-83 - [c87]Ruyu Wang, Sabrina Schmedding, Marco F. Huber:
Improving the Effectiveness of Deep Generative Data. WACV 2024: 4910-4920 - [i45]Benjamin Alt, Florian Stöckl, Silvan Müller, Christopher Braun, Julian Raible, Saad Alhasan, Oliver Rettig, Lukas Ringle, Darko Katic, Rainer Jäkel, Michael Beetz, Marcus Strand, Marco F. Huber:
RoboGrind: Intuitive and Interactive Surface Treatment with Industrial Robots. CoRR abs/2402.16542 (2024) - [i44]Fabian Mauthe, Christopher Braun, Julian Raible, Peter Zeiler, Marco F. Huber:
Overview of Publicly Available Degradation Data Sets for Tasks within Prognostics and Health Management. CoRR abs/2403.13694 (2024) - [i43]Benjamin Frész, Elena Dubovitskaya, Danilo Brajovic, Marco F. Huber, Christian Horz:
How should AI decisions be explained? Requirements for Explanations from the Perspective of European Law. CoRR abs/2404.12762 (2024) - [i42]Florenz Graf, Jochen Lindermayr, Birgit Graf
HIPer: A Human-Inspired Scene Perception Model for Multifunctional Mobile Robots. CoRR abs/2404.17791 (2024) - [i41]Frederic Rapp, David A. Kreplin, Marco F. Huber, Marco Roth:
Reinforcement learning-based architecture search for quantum machine learning. CoRR abs/2406.02717 (2024) - [i40]Patrick Takenaka, Johannes Maucher, Marco F. Huber:
Guiding Video Prediction with Explicit Procedural Knowledge. CoRR abs/2406.18220 (2024) - [i39]Tobias Nagel, Marco F. Huber:
Identifying Ordinary Differential Equations for Data-efficient Model-based Reinforcement Learning. CoRR abs/2406.19817 (2024) - [i38]Patrick Takenaka, Johannes Maucher, Marco F. Huber:
ViPro: Enabling and Controlling Video Prediction for Complex Dynamical Scenarios using Procedural Knowledge. CoRR abs/2407.09537 (2024) - [i37]Benjamin Frész, Vincent Philipp Goebels, Safa Omri, Danilo Brajovic, Andreas Aichele, Janika Kutz, Jens Neuhüttler, Marco F. Huber:
The Contribution of XAI for the Safe Development and Certification of AI: An Expert-Based Analysis. CoRR abs/2408.02379 (2024) - 2023
- [j16]Marc-André Zöller
XAutoML: A Visual Analytics Tool for Understanding and Validating Automated Machine Learning. ACM Trans. Interact. Intell. Syst. 13(4): 28:1-28:39 (2023) - [c86]Philipp Wagner, Xinyang Wu
Kalman Bayesian Neural Networks for Closed-Form Online Learning. AAAI 2023: 10069-10077 - [c85]Julian Raible, Oliver Rettig, Benjamin Alt, Alper Yaman, Isabelle Gauger, Lorenzo Biasi, Silvan Müller, Darko Katic, Marcus Strand, Marco F. Huber:
Artificial Neural Network Guided Compensation of Nonlinear Payload and Wear Effects for Industrial Robots. CASE 2023: 1-8 - [c84]Patrick Takenaka, Johannes Maucher, Marco F. Huber:
Guiding Video Prediction with Explicit Procedural Knowledge. ICCV (Workshops) 2023: 1076-1084 - [c83]Xinyang Wu
Uncertainty-Guided Active Reinforcement Learning with Bayesian Neural Networks. ICRA 2023: 5751-5757 - [c82]Jochen Lindermayr
SynthRetailProduct3D (SyRePro3D): A Pipeline for Synthesis of 3D Retail Product Models with Domain Specific Details Based on Package Class Templates. ICVS 2023: 230-242 - [c81]Kathrin Leiner, Frederic P. Dollmann, Marco F. Huber, Manuel Geiger, Stefan Leinberger:
Cut Interruption Detection in the Laser Cutting Process Using ROCKET on Audio Signals. INDIN 2023: 1-6 - [c80]Jochen Lindermayr, Çagatay Odabasi, Florian Jordan, Florenz Graf, Lukas Knak, Werner Kraus, Richard Bormann, Marco F. Huber:
IPA-3D1K: A Large Retail 3D Model Dataset for Robot Picking. IROS 2023: 11404-11411 - [c79]Xinyang Wu, Elisabeth Wedernikow, Christof Nitsche, Marco F. Huber:
Towards Optimal Energy Management Strategy for Hybrid Electric Vehicle with Reinforcement Learning. IV 2023: 1-7 - [c78]Marc-André Zöller, Fabian Mauthe, Peter Zeiler, Marius Lindauer, Marco F. Huber:
Automated Machine Learning for Remaining Useful Life Predictions. SMC 2023: 2907-2912 - [c77]Christian Jauch, Timo Leitritz, Marco F. Huber:
Self-Supervised Optimization of Hand Pose Estimation Using Anatomical Features and Iterative Learning. SMC 2023: 4519-4524 - [i36]Ruyu Wang, Sabrina Hoppe, Eduardo Monari, Marco F. Huber:
Defect Transfer GAN: Diverse Defect Synthesis for Data Augmentation. CoRR abs/2302.08366 (2023) - [i35]Jannes Elstner, Raoul G. C. Schönhof, Steffen Tauber, Marco F. Huber:
Optimizing CAD Models with Latent Space Manipulation. CoRR abs/2303.12739 (2023) - [i34]Xinyang Wu
Towards Optimal Energy Management Strategy for Hybrid Electric Vehicle with Reinforcement Learning. CoRR abs/2305.12365 (2023) - [i33]Marc-André Zöller, Fabian Mauthe, Peter Zeiler, Marius Lindauer
Automated Machine Learning for Remaining Useful Life Predictions. CoRR abs/2306.12215 (2023) - [i32]Christian Jauch, Timo Leitritz, Marco F. Huber:
Self-supervised Optimization of Hand Pose Estimation using Anatomical Features and Iterative Learning. CoRR abs/2307.03007 (2023) - [i31]Danilo Brajovic, Niclas Renner, Vincent Philipp Goebels, Philipp Wagner, Benjamin Frész, Martin Biller, Mara Klaeb, Janika Kutz, Jens Neuhüttler, Marco F. Huber:
Model Reporting for Certifiable AI: A Proposal from Merging EU Regulation into AI Development. CoRR abs/2307.11525 (2023) - [i30]Ruyu Wang, Sabrina Schmedding, Marco F. Huber:
Improving the Effectiveness of Deep Generative Data. CoRR abs/2311.03959 (2023) - [i29]Marc-André Zöller, Marius Lindauer, Marco F. Huber:
auto-sktime: Automated Time Series Forecasting. CoRR abs/2312.08528 (2023) - [i28]Danilo Brajovic, Marco F. Huber:
Merging Explainable AI into Automotive Software Development. ERCIM News 2023(134) (2023) - 2022
- [j15]Nadia Burkart, Danilo Brajovic, Marco F. Huber:
Explainable AI: introducing trust and comprehensibility to AI engineering. Autom. 70(9): 787-792 (2022) - [j14]Manjunatha Veerappa
Validation of XAI explanations for multivariate time series classification in the maritime domain. J. Comput. Sci. 58: 101539 (2022) - [j13]Florenz Graf
Toward Holistic Scene Understanding: A Transfer of Human Scene Perception to Mobile Robots. IEEE Robotics Autom. Mag. 29(4): 36-49 (2022) - [c76]Ruyu Wang, Sabrina Hoppe, Eduardo Monari, Marco F. Huber:
Defect Transfer GAN: Diverse Defect Synthesis for Data Augmentation. BMVC 2022: 445 - [c75]Tobias Nagel
Kalman-Bucy-Informed Neural Network for System Identification. CDC 2022: 1503-1508 - [c74]Mohamed El-Shamouty, Julian Titze, Sitar Kortik, Werner Kraus, Marco F. Huber:
GLIR: A Practical Global-local Integrated Reactive Planner towards Safe Human-Robot Collaboration. ETFA 2022: 1-8 - [c73]Pascal Weller, Fady Aziz, Sherif Abdulatif, Urs Schneider, Marco F. Huber:
A MIMO Radar-based Few-Shot Learning Approach for Human-ID. EUSIPCO 2022: 1796-1800 - [c72]Simeon Brüggenjürgen, Nina Schaaf, Pascal Kerschke
Mixture of Decision Trees for Interpretable Machine Learning. ICMLA 2022: 1175-1182 - [c71]Marius Moosmann, Felix Spenrath, Johannes Rosport, Philipp Melzer, Werner Kraus, Richard Bormann, Marco F. Huber:
Transfer Learning for Machine Learning-based Detection and Separation of Entanglements in Bin-Picking Applications. IROS 2022: 1123-1130 - [c70]Arik Lämmle, Philipp Tenbrock, Balázs András Bálint, Frank Nägele, Werner Kraus, József Váncza, Marco F. Huber:
Simulation-based Learning of the Peg-in-Hole Process Using Robot-Skills. IROS 2022: 9340-9346 - [c69]Christoph Hennebold, Xiaodong Mei, Ortwin Mailahn, Marco F. Huber, Oliver Mannuß:
Cooperation of Human and Active Learning based AI for Fast and Precise Complaint Management. SMC 2022: 282-287 - [i27]Raoul Schönhof, Artem Werner, Jannes Elstner, Boldizsar Zopcsak, Ramez Awad, Marco F. Huber:
Feature Visualization within an Automated Design Assessment leveraging Explainable Artificial Intelligence Methods. CoRR abs/2201.12107 (2022) - [i26]Raoul Schönhof, Jannes Elstner, Radu Manea, Steffen Tauber, Ramez Awad, Marco F. Huber:
Simplified Learning of CAD Features Leveraging a Deep Residual Autoencoder. CoRR abs/2202.10099 (2022) - [i25]Marc-André Zöller, Waldemar Titov, Thomas Schlegel, Marco F. Huber:
XAutoML: A Visual Analytics Tool for Establishing Trust in Automated Machine Learning. CoRR abs/2202.11954 (2022) - [i24]Paul-Amaury Matt, Rosina Ziegler, Danilo Brajovic, Marco Roth, Marco F. Huber:
A Nested Genetic Algorithm for Explaining Classification Data Sets with Decision Rules. CoRR abs/2209.07575 (2022) - [i23]Tobias Nagel, Marco F. Huber:
Kalman-Bucy-Informed Neural Network for System Identification. CoRR abs/2210.03424 (2022) - [i22]Simeon Brüggenjürgen, Nina Schaaf, Pascal Kerschke, Marco F. Huber:
Mixture of Decision Trees for Interpretable Machine Learning. CoRR abs/2211.14617 (2022) - 2021
- [j12]Nadia Burkart
Are you sure? Prediction revision in automated decision-making. Expert Syst. J. Knowl. Eng. 38(1) (2021) - [j11]Nadia Burkart, Marco F. Huber:
A Survey on the Explainability of Supervised Machine Learning. J. Artif. Intell. Res. 70: 245-317 (2021) - [j10]Marc-André Zöller
Benchmark and Survey of Automated Machine Learning Frameworks. J. Artif. Intell. Res. 70: 409-472 (2021) - [j9]Christian Landgraf
A Reinforcement Learning Approach to View Planning for Automated Inspection Tasks. Sensors 21(6): 2030 (2021) - [c68]Christian Jauch
Generating a Hand Pose Data Set for Vision Based Manual Assembly Assistance Systems. 3D Imaging and Applications 2021: 1-7 - [c67]Simon Dürr
Reinforcement Learning based Optimization of Bayesian Networks for Generating Feasible Vehicle Configuration Suggestions. CASE 2021: 16-22 - [c66]Christian Landgraf, Kilian Ernst, Gesine Schleth, Marc Fabritius
A Hybrid Neural Network Approach for Increasing the Absolute Accuracy of Industrial Robots. CASE 2021: 468-474 - [c65]Tobias Nagel
Autoencoder-Inspired Identification of LTI Systems. ECC 2021: 2352-2357 - [c64]Fady Aziz, Bassam Elmakhzangy, Christophe Maufroy, Urs Schneider, Marco F. Huber:
DimRad: A Radar-Based Perception System for Prosthetic Leg Barrier Traversing. EUSIPCO 2021: 1750-1754 - [c63]Kilian Kleeberger, Florian Roth, Richard Bormann, Marco F. Huber:
Automatic Grasp Pose Generation for Parallel Jaw Grippers. IAS 2021: 594-607 - [c62]Nina Schaaf
Towards Measuring Bias in Image Classification. ICANN (3) 2021: 433-445 - [c61]Kilian Kleeberger, Markus Völk, Richard Bormann, Marco F. Huber:
Investigations on Output Parameterizations of Neural Networks for Single Shot 6D Object Pose Estimation. ICRA 2021: 13916-13922 - [c60]Marc-André Zöller
Incremental Search Space Construction for Machine Learning Pipeline Synthesis. IDA 2021: 103-115 - [c59]Raphael Lamprecht
Reinforcement Learning based Condition-oriented Maintenance Scheduling for Flow Line Systems. INDIN 2021: 1-7 - [c58]Kilian Kleeberger, Jonathan Schnitzler, Muhammad Usman Khalid, Richard Bormann, Werner Kraus
Precise Object Placement with Pose Distance Estimations for Different Objects and Grippers. IROS 2021: 4639-4646 - [c57]Daniel Bargmann
Unobstructed Programming-by-Demonstration for Force-Based Assembly Utilizing External Force-Torque Sensors. SMC 2021: 119-124 - [i21]Kilian Kleeberger, Markus Völk, Marius Moosmann, Erik Thiessenhusen, Florian Roth, Richard Bormann, Marco F. Huber:
Transferring Experience from Simulation to the Real World for Precise Pick-And-Place Tasks in Highly Cluttered Scenes. CoRR abs/2101.04781 (2021) - [i20]Marc-André Zöller, Tien-Dung Nguyen, Marco F. Huber:
Incremental Search Space Construction for Machine Learning Pipeline Synthesis. CoRR abs/2101.10951 (2021) - [i19]Kilian Kleeberger, Markus Völk, Richard Bormann, Marco F. Huber:
Investigations on Output Parameterizations of Neural Networks for Single Shot 6D Object Pose Estimation. CoRR abs/2104.07528 (2021) - [i18]Kilian Kleeberger, Florian Roth, Richard Bormann, Marco F. Huber:
Automatic Grasp Pose Generation for Parallel Jaw Grippers. CoRR abs/2104.11660 (2021) - [i17]Fady Aziz, Bassam Elmakhzangy, Christophe Maufroy, Urs Schneider, Marco F. Huber:
DimRad: A Radar-Based Perception System for Prosthetic Leg Barrier Traversing. CoRR abs/2105.14634 (2021) - [i16]Nina Schaaf, Omar de Mitri, Hang Beom Kim, Alexander Windberger, Marco F. Huber:
Towards Measuring Bias in Image Classification. CoRR abs/2107.00360 (2021) - [i15]Raphael Lamprecht, Ferdinand Wurst, Marco F. Huber:
Reinforcement Learning based Condition-oriented Maintenance Scheduling for Flow Line Systems. CoRR abs/2108.12298 (2021) - [i14]Philipp Wagner, Xinyang Wu, Marco F. Huber:
Kalman Bayesian Neural Networks for Closed-form Online Learning. CoRR abs/2110.00944 (2021) - [i13]Kilian Kleeberger, Jonathan Schnitzler, Muhammad Usman Khalid, Richard Bormann, Werner Kraus, Marco F. Huber:
Precise Object Placement with Pose Distance Estimations for Different Objects and Grippers. CoRR abs/2110.00992 (2021) - [i12]Pascal Weller, Fady Aziz, Sherif Abdulatif, Urs Schneider, Marco F. Huber:
A MIMO Radar-based Few-Shot Learning Approach for Human-ID. CoRR abs/2110.08595 (2021) - [i11]Fady Aziz, Omar Metwally, Pascal Weller, Urs Schneider, Marco F. Huber:
A MIMO Radar-Based Metric Learning Approach for Activity Recognition. CoRR abs/2111.01939 (2021) - 2020
- [c56]Marco F. Huber:
Bayesian Perceptron: Towards fully Bayesian Neural Networks. CDC 2020: 3179-3186 - [c55]Mohamed El-Shamouty, Xinyang Wu
Towards Safe Human-Robot Collaboration Using Deep Reinforcement Learning. ICRA 2020: 4899-4905 - [c54]Kilian Kleeberger, Marco F. Huber
Single Shot 6D Object Pose Estimation. ICRA 2020: 6239-6245 - [c53]Kilian Kleeberger, Markus Völk, Marius Moosmann, Erik Thiessenhusen, Florian Roth, Richard Bormann, Marco F. Huber:
Transferring Experience from Simulation to the Real World for Precise Pick-And-Place Tasks in Highly Cluttered Scenes. IROS 2020: 9681-9688 - [c52]Nadia Burkart, Philipp Michael Faller, Elisabeth Peinsipp, Marco F. Huber
Batch-wise Regularization of Deep Neural Networks for Interpretability. MFI 2020: 216-222 - [c51]Nadia Burkart, Marco F. Huber
Supported Decision-Making by Explainable Predictions of Ship Trajectories. SOCO 2020: 44-54 - [i10]Kilian Kleeberger, Marco F. Huber:
Single Shot 6D Object Pose Estimation. CoRR abs/2004.12729 (2020) - [i9]Marco F. Huber:
Bayesian Perceptron: Towards fully Bayesian Neural Networks. CoRR abs/2009.01730 (2020) - [i8]Nadia Burkart, Marco F. Huber:
A Survey on the Explainability of Supervised Machine Learning. CoRR abs/2011.07876 (2020)
2010 – 2019
- 2019
- [c50]Muhammad Usman Khalid, Janik M. Hager, Werner Kraus
Deep Workpiece Region Segmentation for Bin Picking. CASE 2019: 1138-1144 - [c49]Nina Schaaf, Marco F. Huber
Enhancing Decision Tree Based Interpretation of Deep Neural Networks through L1-Orthogonal Regularization. ICMLA 2019: 42-49 - [c48]Nadia Burkart, Marco F. Huber
Forcing Interpretability for Deep Neural Networks through Rule-Based Regularization. ICMLA 2019: 700-705 - [c47]Patrick Dunau, Marco F. Huber
Gaussian Process based Dynamic Facial Emotion Tracking. ICPS 2019: 248-253 - [c46]Kilian Kleeberger, Christian Landgraf, Marco F. Huber
Large-scale 6D Object Pose Estimation Dataset for Industrial Bin-Picking. IROS 2019: 2573-2578 - [c45]Nadia El Bekri, Jasmin Kling, Marco F. Huber
A Study on Trust in Black Box Models and Post-hoc Explanations. SOCO 2019: 35-46 - [i7]Nina Schaaf, Marco F. Huber:
Enhancing Decision Tree based Interpretation of Deep Neural Networks through L1-Orthogonal Regularization. CoRR abs/1904.05394 (2019) - [i6]Marc-André Zöller, Marco F. Huber:
Survey on Automated Machine Learning. CoRR abs/1904.12054 (2019) - [i5]Muhammad Usman Khalid, Janik M. Hager, Werner Kraus, Marco F. Huber, Marc Toussaint:
Deep Workpiece Region Segmentation for Bin Picking. CoRR abs/1909.03462 (2019) - [i4]Kilian Kleeberger, Christian Landgraf, Marco F. Huber:
Large-scale 6D Object Pose Estimation Dataset for Industrial Bin-Picking. CoRR abs/1912.12125 (2019) - 2018
- [j8]Marco F. Huber
Linear programming based time lag identification in event sequences. Autom. 98: 14-19 (2018) - [j7]Uwe D. Hanebeck
Guest Editorial Special Section on Multisensor Fusion and Integration for Intelligent Systems. IEEE Trans. Ind. Informatics 14(3): 1124-1126 (2018) - [c44]Patrick Dunau, Marco F. Huber
Comparison of Angle and Size Features with Deep Learning for Emotion Recognition. CIARP 2018: 602-610 - [c43]Selim Ozgen, Florian Rosenthal
Retrodiction of Data Association Probabilities via Convex Optimization. FUSION 2018: 2430-2436 - [c42]Patrick Dunau, Mike Bonny, Marco F. Huber
Reduced Feature Set for Emotion Recognition Based on Angle and Size Information. IAS 2018: 585-596 - 2017
- [j6]Marco F. Huber
Conditional anomaly detection in event streams. Autom. 65(4): 233 (2017) - [c41]Marc-Andre Zoller, Marcus Baum
Framework for mining event correlations and time lags in large event sequences. INDIN 2017: 805-810 - 2016
- [c40]Marco F. Huber, Martin Voigt, Axel-Cyrille Ngonga Ngomo
Big data architecture for the semantic analysis of complex events in manufacturing. GI-Jahrestagung 2016: 353-360 - [c39]Marco F. Huber
Bayesian score level fusion for facial recognition. MFI 2016: 371-378 - 2015
- [c38]Jason R. Rambach, Marco F. Huber
Collaborative multi-camera face recognition and tracking. AVSS 2015: 1-6 - [c37]Vangelis Gazis
Short Paper: IoT: Challenges, projects, architectures. ICIN 2015: 145-147 - [c36]Vangelis Gazis
A survey of technologies for the internet of things. IWCMC 2015: 1090-1095 - 2014
- [j5]Marco F. Huber
Recursive Gaussian process: On-line regression and learning. Pattern Recognit. Lett. 45: 85-91 (2014) - [c35]Michael Teutsch
Low Resolution Person Detection with a Moving Thermal Infrared Camera by Hot Spot Classification. CVPR Workshops 2014: 209-216 - [c34]Florian Zeiger, Marco F. Huber:
Demonstration abstract: participatory sensing enabled environmental monitoring in smart cities. IPSN 2014: 337-338 - 2013
- [j4]Marco F. Huber
Chebyshev polynomial Kalman filter. Digit. Signal Process. 23(5): 1620-1629 (2013) - [c33]Marco F. Huber, Uwe D. Hanebeck:
Gaussian filtering for polynomial systems based on moment homotopy. FUSION 2013: 1080-1087 - [c32]Marco F. Huber
Recursive Gaussian process regression. ICASSP 2013: 3362-3366 - [c31]Alexey Pak, Marco F. Huber
On weak distance between distributions in application to tracking. SDF 2013: 1-6 - 2012
- [j3]Marco F. Huber
Optimal Pruning for Multi-Step Sensor Scheduling. IEEE Trans. Autom. Control. 57(5): 1338-1343 (2012) - [j2]Marc Peter Deisenroth, Ryan D. Turner, Marco F. Huber
Robust Filtering and Smoothing with Gaussian Processes. IEEE Trans. Autom. Control. 57(7): 1865-1871 (2012) - [c30]Marco F. Huber, Tobias Dencker, Masoud Roschani, Jürgen Beyerer:
Bayesian active object recognition via Gaussian process regression. FUSION 2012: 1718-1725 - [i3]Marc Peter Deisenroth, Ryan D. Turner, Marco F. Huber, Uwe D. Hanebeck, Carl Edward Rasmussen:
Robust Filtering and Smoothing with Gaussian Processes. CoRR abs/1203.4345 (2012) - [i2]Marco F. Huber:
Optimal Pruning for Multi-Step Sensor Scheduling. CoRR abs/1203.6243 (2012) - [i1]Marco F. Huber:
Adaptive Gaussian Mixture Filter Based on Statistical Linearization. CoRR abs/1203.6750 (2012) - 2011
- [c29]Marco F. Huber
Semi-analytic Gaussian Assumed Density Filter. ACC 2011: 3006-3011 - [c28]Marco F. Huber:
Adaptive Gaussian mixture filter based on statistical linearization. FUSION 2011: 1-8 - [c27]Marco F. Huber, Peter Krauthausen, Uwe D. Hanebeck:
Superficial Gaussian Mixture Reduction. GI-Jahrestagung 2011: 491 - 2010
- [c26]Marco F. Huber
On multi-step sensor scheduling via convex optimization. CIP 2010: 376-381 - [c25]Peter Krauthausen, Marco F. Huber, Uwe D. Hanebeck:
Support-vector conditional density estimation for nonlinear filtering. FUSION 2010: 1-8 - [c24]Achim Kuwertz, Marco F. Huber, Felix Sawo:
Multi-step sensor management for localizing movable sources of spatially distributed phenomena. FUSION 2010: 1-8 - [c23]Frederik Beutler, Marco F. Huber
Optimal stochastic linearization for range-based localization. IROS 2010: 5731-5736 - [c22]Frederik Beutler, Marco F. Huber
Semi-analytic stochastic linearization for range-based pose tracking. MFI 2010: 44-49
2000 – 2009
- 2009
- [b1]Marco F. Huber:
Probabilistic Framework for Sensor Management. Karlsruhe University, Germany, 2009 - [j1]Frederik Beutler, Marco F. Huber
Probabilistic instantaneous model-based signal processing applied to localization and tracking. Robotics Auton. Syst. 57(3): 249-258 (2009) - [c21]Uwe D. Hanebeck, Marco F. Huber
Dirac mixture approximation of multivariate Gaussian densities. CDC 2009: 3851-3858 - [c20]Marco F. Huber, Achim Kuwertz, Felix Sawo, Uwe D. Hanebeck:
Distributed greedy sensor scheduling for model-based reconstruction of space-time continuous physical phenomena. FUSION 2009: 102-109 - [c19]Frederik Beutler, Marco F. Huber, Uwe D. Hanebeck:
Gaussian Filtering using state decomposition methods. FUSION 2009: 579-586 - [c18]Dennis Schieferdecker, Marco F. Huber:
Gaussian mixture reduction via clustering. FUSION 2009: 1536-1543 - [c17]Frederik Beutler, Marco F. Huber
Instantaneous pose estimation using rotation vectors. ICASSP 2009: 3413-3416 - [c16]Marc Peter Deisenroth, Marco F. Huber
Analytic moment-based Gaussian process filtering. ICML 2009: 225-232 - 2008
- [c15]Marco F. Huber, Uwe D. Hanebeck:
Progressive Gaussian mixture reduction. FUSION 2008: 1-8 - [c14]Marco F. Huber, Uwe D. Hanebeck:
Priority list sensor scheduling using optimal pruning. FUSION 2008: 1-8 - [c13]Florian Weissel, Thomas Schreiter, Marco F. Huber
Stochastic model predictive control of time-variant nonlinear systems with imperfect state information. MFI 2008: 40-46 - [c12]Marco F. Huber
On entropy approximation for Gaussian mixture random vectors. MFI 2008: 181-188 - 2007
- [c11]Florian Weissel, Marco F. Huber
Efficient Control of Nonlinear Noise-Corrupted Systems Using a Novel Model Predictive Control Framework. ACC 2007: 3751-3756 - [c10]Marco F. Huber
Efficient Nonlinear Measurement Updating based on Gaussian Mixture Approximation of Conditional Densities. ACC 2007: 4425-4430 - [c9]Florian Weissel, Marco F. Huber
A nonlinear model predictive control framework approximating noise corrupted systems with hybrid transition densities. CDC 2007: 3661-3666 - [c8]Marco F. Huber
The hybrid density filter for nonlinear estimation based on hybrid conditional density approximation. FUSION 2007: 1-8 - [c7]Felix Sawo, Marco F. Huber
Parameter identification and reconstruction for distributed phenomena based on hybrid density filter. FUSION 2007: 1-8 - [c6]Marco F. Huber, Eric Stiegeler, Uwe D. Hanebeck:
On Sensor Scheduling in Case of Unreliable Communication. GI Jahrestagung (2) 2007: 90-94 - [c5]Florian Weissel, Marco F. Huber, Uwe D. Hanebeck:
A closed-form model predictive control framework for nonlinear noise-corrupted systems. ICINCO-SPSMC 2007: 62-69 - [c4]Marco F. Huber
Hybrid transition density approximation for efficient recursive prediction of nonlinear dynamic systems. IPSN 2007: 283-292 - [c3]Florian Weissel, Marco F. Huber
Test-environment based on a team of miniature walking robots for evaluation of collaborative control methods. IROS 2007: 2474-2479 - 2006
- [c2]Marco F. Huber
Closed-Form Prediction of Nonlinear Dynamic Systems by Means of Gaussian Mixture Approximation of the Transition Density. MFI 2006: 98-103 - 2005
- [c1]Bernd Gaßmann, Marco F. Huber, Johann Marius Zöllner, Rüdiger Dillmann:
Navigation of Walking Robots: Path Planning. CLAWAR 2005: 115-122
Coauthor Index
Marc-André Zöller
aka: Marc-Andre Zoller
aka: Marc-Andre Zoller
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