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Michael Hefenbrock
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2020 – today
- 2025
- [j11]Vincent Meyers, Michael Hefenbrock, Dennis Gnad, Mehdi B. Tahoori:
Leveraging Neural Trojan Side-Channels for Output Exfiltration. Cryptogr. 9(1): 5 (2025) - [j10]Dina A. Moussa
, Michael Hefenbrock
Compressed Test Pattern Generation for Deep Neural Networks. IEEE Trans. Computers 74(1): 307-315 (2025) - [c37]Vincent Meyers
Towards Functional Safety of Neural Network Hardware Accelerators: Concurrent Out-of-Distribution Detection in Hardware Using Power Side-Channel Analysis. ASP-DAC 2025: 1413-1419 - 2024
- [j9]Dina A. Moussa
Testing for Multiple Faults in Deep Neural Networks. IEEE Des. Test 41(3): 47-53 (2024) - [j8]Soyed Tuhin Ahmed
Design-time Reference Current Generation for Robust Spintronic-based Neuromorphic Architecture. ACM J. Emerg. Technol. Comput. Syst. 20(1): 2:1-2:20 (2024) - [c36]Florentia Afentaki, Michael Hefenbrock, Georgios Zervakis, Mehdi B. Tahoori:
Embedding Hardware Approximations in Discrete Genetic-Based Training for Printed MLPs. DATE 2024: 1-6 - [c35]Priyanjana Pal, Haibin Zhao, Maha Shatta, Michael Hefenbrock, Sina Bakhtavari Mamaghani, Sani R. Nassif, Michael Beigl, Mehdi B. Tahoori:
Analog Printed Spiking Neuromorphic Circuit. DATE 2024: 1-6 - [c34]Soyed Tuhin Ahmed
Testing Spintronics Implemented Monte Carlo Dropout-Based Bayesian Neural Networks. ETS 2024: 1-6 - [c33]Priyanjana Pal
Fault Sensitivity Analysis of Printed Bespoke Multilayer Perceptron Classifiers. ETS 2024: 1-6 - [c32]Vincent Meyers
Trained to Leak: Hiding Trojan Side-Channels in Neural Network Weights. HOST 2024: 122-127 - [c31]Soyed Tuhin Ahmed
Tiny Deep Ensemble: Uncertainty Estimation in Edge AI Accelerators via Ensembling Normalization Layers with Shared Weights. ICCAD 2024: 71:1-71:9 - [c30]Priyanjana Pal
Neural Architecture Search for Highly Bespoke Robust Printed Neuromorphic Circuits. ICCAD 2024: 230:1-230:9 - [c29]Yexu Zhou, Haibin Zhao, Michael Hefenbrock, Siyan Li, Yiran Huang, Michael Beigl:
Deep Neural Network Pruning with Progressive Regularizer. IJCNN 2024: 1-10 - [c28]Jörg K. H. Franke, Michael Hefenbrock, Gregor Köhler, Frank Hutter:
Improving Deep Learning Optimization through Constrained Parameter Regularization. NeurIPS 2024 - [i10]Soyed Tuhin Ahmed
Testing Spintronics Implemented Monte Carlo Dropout-Based Bayesian Neural Networks. CoRR abs/2401.04744 (2024) - [i9]Florentia Afentaki, Michael Hefenbrock, Georgios Zervakis
Embedding Hardware Approximations in Discrete Genetic-based Training for Printed MLPs. CoRR abs/2402.02930 (2024) - [i8]Soyed Tuhin Ahmed, Michael Hefenbrock, Mehdi B. Tahoori:
Tiny Deep Ensemble: Uncertainty Estimation in Edge AI Accelerators via Ensembling Normalization Layers with Shared Weights. CoRR abs/2405.05286 (2024) - 2023
- [j7]Soyed Tuhin Ahmed
NeuroScrub+: Mitigating Retention Faults Using Flexible Approximate Scrubbing in Neuromorphic Fabric Based on Resistive Memories. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(5): 1490-1503 (2023) - [j6]Soyed Tuhin Ahmed
SpinBayes: Algorithm-Hardware Co-Design for Uncertainty Estimation Using Bayesian In-Memory Approximation on Spintronic-Based Architectures. ACM Trans. Embed. Comput. Syst. 22(5s): 131:1-131:25 (2023) - [c27]Dina A. Moussa, Michael Hefenbrock, Christopher Münch, Mehdi B. Tahoori:
Automatic Test Pattern Generation and Compaction for Deep Neural Networks. ASP-DAC 2023: 436-441 - [c26]Soyed Tuhin Ahmed, Kamal Danouchi
Scalable Spintronics-based Bayesian Neural Network for Uncertainty Estimation. DATE 2023: 1-6 - [c25]Dina A. Moussa, Michael Hefenbrock, Mehdi B. Tahoori:
Compact Test Pattern Generation For Multiple Faults In Deep Neural Networks. DATE 2023: 1-2 - [c24]Haibin Zhao
Split Additive Manufacturing for Printed Neuromorphic Circuits. DATE 2023: 1-6 - [c23]Haibin Zhao, Brojogopal Sapui, Michael Hefenbrock, Zhidong Yang, Michael Beigl, Mehdi B. Tahoori:
Highly-Bespoke Robust Printed Neuromorphic Circuits. DATE 2023: 1-6 - [c22]Vincent Meyers, Michael Hefenbrock, Dennis Gnad
Remote Identification of Neural Network FPGA Accelerators by Power Fingerprints. FPL 2023: 259-264 - [c21]Haibin Zhao
Power-Aware Training for Energy-Efficient Printed Neuromorphic Circuits. ICCAD 2023: 1-9 - [c20]Yiran Huang, Nicole Schaal, Michael Hefenbrock, Yexu Zhou, Till Riedel
McXai: Local Model-Agnostic Explanation As Two Games. IJCNN 2023: 1-8 - [c19]Haibin Zhao
Towards Temporal Information Processing - Printed Neuromorphic Circuits with Learnable Filters. NANOARCH 2023: 12:1-12:6 - [i7]Soyed Tuhin Ahmed, Kamal Danouchi, Michael Hefenbrock, Guillaume Prenat, Lorena Anghel, Mehdi B. Tahoori:
Spatial-SpinDrop: Spatial Dropout-based Binary Bayesian Neural Network with Spintronics Implementation. CoRR abs/2306.10185 (2023) - [i6]Jörg K. H. Franke, Michael Hefenbrock, Gregor Köhler, Frank Hutter:
New Horizons in Parameter Regularization: A Constraint Approach. CoRR abs/2311.09058 (2023) - [i5]Soyed Tuhin Ahmed, Kamal Danouchi, Michael Hefenbrock, Guillaume Prenat, Lorena Anghel, Mehdi B. Tahoori:
Scale-Dropout: Estimating Uncertainty in Deep Neural Networks Using Stochastic Scale. CoRR abs/2311.15816 (2023) - 2022
- [b1]Michael Hefenbrock:
Modelling and Training Printed Neuromorphic Circuits. Karlsruhe University, Germany, 2022 - [j5]Ahmet Turan Erozan, Michael Hefenbrock, Dennis R. E. Gnad
Counterfeit Detection and Prevention in Additive Manufacturing Based on Unique Identification of Optical Fingerprints of Printed Structures. IEEE Access 10: 105910-105919 (2022) - [j4]Dennis D. Weller
Fast and Efficient High-Sigma Yield Analysis and Optimization Using Kernel Density Estimation on a Bayesian Optimized Failure Rate Model. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41(3): 695-708 (2022) - [c18]Michael Hefenbrock, Dennis D. Weller, Jasmin Aghassi-Hagmann
In-situ Tuning of Printed Neural Networks for Variation Tolerance. DATE 2022: 72-75 - [c17]Soyed Tuhin Ahmed
Process and Runtime Variation Robustness for Spintronic-Based Neuromorphic Fabric. ETS 2022: 1-2 - [c16]Haibin Zhao
Aging-Aware Training for Printed Neuromorphic Circuits. ICCAD 2022: 38:1-38:9 - [c15]Yiran Huang, Yexu Zhou, Michael Hefenbrock, Till Riedel
Universal Distributional Decision-Based Black-Box Adversarial Attack with Reinforcement Learning. ICONIP (3) 2022: 206-215 - [c14]Haibin Zhao
Improving Human Activity Recognition Models by Learnable Sparse Wavelet Layer. ISWC 2022: 84-88 - [c13]Yexu Zhou
TinyHAR: A Lightweight Deep Learning Model Designed for Human Activity Recognition. ISWC 2022: 89-93 - [c12]Yiran Huang
Automatic Feature Engineering Through Monte Carlo Tree Search. ECML/PKDD (3) 2022: 581-598 - [i4]Yiran Huang, Nicole Schaal, Michael Hefenbrock, Yexu Zhou, Till Riedel
McXai: Local model-agnostic explanation as two games. CoRR abs/2201.01044 (2022) - [i3]Yiran Huang, Yexu Zhou, Michael Hefenbrock, Till Riedel
Universal Distributional Decision-based Black-box Adversarial Attack with Reinforcement Learning. CoRR abs/2211.08384 (2022) - 2021
- [c11]Tobias Röddiger, Michael Beigl, Michael Hefenbrock, Daniel Wolffram, Erik Pescara:
Detecting Episodes of Increased Cough Using Kinetic Earables. AHs 2021: 111-115 - [c10]Dennis D. Weller, Nathaniel Bleier
Printed Stochastic Computing Neural Networks. DATE 2021: 914-919 - [c9]Soyed Tuhin Ahmed
NeuroScrub: Mitigating Retention Failures Using Approximate Scrubbing in Neuromorphic Fabric Based on Resistive Memories. ETS 2021: 1-6 - 2020
- [j3]Farhan Rasheed, Michael Hefenbrock, Rajendra Bishnoi, Michael Beigl, Jasmin Aghassi-Hagmann, Mehdi Baradaran Tahoori:
Crossover-aware Placement and Routing for Inkjet Printed Circuits. ACM J. Emerg. Technol. Comput. Syst. 16(2): 19:1-19:22 (2020) - [j2]Dennis D. Weller
Bayesian Optimized Mixture Importance Sampling for High-Sigma Failure Rate Estimation. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(10): 2772-2783 (2020) - [j1]Ahmet Turan Erozan
Reverse Engineering of Printed Electronics Circuits: From Imaging to Netlist Extraction. IEEE Trans. Inf. Forensics Secur. 15: 475-486 (2020) - [c8]Dennis D. Weller, Michael Hefenbrock, Mehdi Baradaran Tahoori, Jasmin Aghassi-Hagmann, Michael Beigl:
Programmable Neuromorphic Circuit based on Printed Electrolyte-Gated Transistors. ASP-DAC 2020: 446-451 - [c7]Michael Hefenbrock, Dennis D. Weller, Michael Beigl, Mehdi Baradaran Tahoori:
Fast and Accurate High-Sigma Failure Rate Estimation through Extended Bayesian Optimized Importance Sampling. DATE 2020: 103-108 - [c6]Yuma Tsurugasaki, Koichi Shimoda, Michael Hefenbrock, Akihito Taya
Scalable selection of EEG features for compression. UbiComp/ISWC Adjunct 2020: 712-715 - [c5]Yexu Zhou, Michael Hefenbrock, Yiran Huang
Automatic Remaining Useful Life Estimation Framework with Embedded Convolutional LSTM as the Backbone. ECML/PKDD (4) 2020: 461-477 - [i2]Yexu Zhou, Yuting Gao, Yiran Huang, Michael Hefenbrock, Till Riedel
Automatic Remaining Useful Life Estimation Framework with Embedded Convolutional LSTM as the Backbone. CoRR abs/2008.03961 (2020)
2010 – 2019
- 2019
- [c4]Farhan Rasheed, Michael Hefenbrock, Rajendra Bishnoi, Michael Beigl, Jasmin Aghassi-Hagmann
Predictive Modeling and Design Automation of Inorganic Printed Electronics. DATE 2019: 30-35 - [c3]Dennis D. Weller, Michael Hefenbrock, Mohammad Saber Golanbari, Michael Beigl, Mehdi Baradaran Tahoori:
Bayesian Optimized Importance Sampling for High Sigma Failure Rate Estimation. DATE 2019: 1667-1672 - [c2]Yuma Tsurugasaki, Katsuhiro Mori, Michael Hefenbrock, Yoshito Tobe:
Identification of Effective EEG Electrodes for Depression Sensing. Intelligent Environments (Workshops) 2019: 152-161 - [i1]Ahmet Turan Erozan, Michael Hefenbrock, Michael Beigl, Jasmin Aghassi-Hagmann, Mehdi Baradaran Tahoori:
Image PUF: A Physical Unclonable Function for Printed Electronics based on Optical Variation of Printed Inks. IACR Cryptol. ePrint Arch. 2019: 1419 (2019) - 2018
- [c1]Erik Pescara
Vibration Personalization with Evolutionary Algorithms. UbiComp/ISWC Adjunct 2018: 436-439
Coauthor Index
aka: Mehdi B. Tahoori
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last updated on 2025-05-05 20:51 CEST by the dblp team
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