Vibration Personalization with Evolutionary Algorithms. - Erik Pescara; Michael Hefenbrock; Thomas Rzepka; Michael Beigl (UbiComp/ISWC Adjunct, 2018)

Predictive Modeling and Design Automation of Inorganic Printed Electronics. - Farhan Rasheed; Michael Hefenbrock; Rajendra Bishnoi; Michael Beigl; Jasmin Aghassi-Hagmann; Mehdi Baradaran Tahoori (DATE, 2019)

Bayesian Optimized Importance Sampling for High Sigma Failure Rate Estimation. - Dennis D. Weller; Michael Hefenbrock; Mohammad Saber Golanbari; Michael Beigl; Mehdi Baradaran Tahoori (DATE, 2019)

Identification of Effective EEG Electrodes for Depression Sensing. - Yuma Tsurugasaki; Katsuhiro Mori; Michael Hefenbrock; Yoshito Tobe (Intelligent Environments (Workshops), 2019)

Image PUF: A Physical Unclonable Function for Printed Electronics based on Optical Variation of Printed Inks. - Ahmet Turan Erozan; Michael Hefenbrock; Michael Beigl; Jasmin Aghassi-Hagmann; Mehdi Baradaran Tahoori (IACR Cryptol. ePrint Arch., 2019)

Programmable Neuromorphic Circuit based on Printed Electrolyte-Gated Transistors. - Dennis D. Weller; Michael Hefenbrock; Mehdi Baradaran Tahoori; Jasmin Aghassi-Hagmann; Michael Beigl (ASP-DAC, 2020)

Fast and Accurate High-Sigma Failure Rate Estimation through Extended Bayesian Optimized Importance Sampling. - Michael Hefenbrock; Dennis D. Weller; Michael Beigl; Mehdi Baradaran Tahoori (DATE, 2020)

Scalable selection of EEG features for compression. - Yuma Tsurugasaki; Koichi Shimoda; Michael Hefenbrock; Akihito Taya; Sejun Song; Yoshito Tobe (UbiComp/ISWC Adjunct, 2020)

Automatic Remaining Useful Life Estimation Framework with Embedded Convolutional LSTM as the Backbone. - Yexu Zhou; Michael Hefenbrock; Yiran Huang; Till Riedel; Michael Beigl (ECML/PKDD (4), 2020)

Automatic Remaining Useful Life Estimation Framework with Embedded Convolutional LSTM as the Backbone. - Yexu Zhou; Yuting Gao; Yiran Huang; Michael Hefenbrock; Till Riedel; Michael Beigl (CoRR, 2020)

Crossover-aware Placement and Routing for Inkjet Printed Circuits. - Farhan Rasheed; Michael Hefenbrock; Rajendra Bishnoi; Michael Beigl; Jasmin Aghassi-Hagmann; Mehdi Baradaran Tahoori (ACM J. Emerg. Technol. Comput. Syst., 2020)

Bayesian Optimized Mixture Importance Sampling for High-Sigma Failure Rate Estimation. - Dennis D. Weller; Michael Hefenbrock; Mohammad Saber Golanbari; Michael Beigl; Jasmin Aghassi-Hagmann; Mehdi B. Tahoori (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2020)

Reverse Engineering of Printed Electronics Circuits: From Imaging to Netlist Extraction. - Ahmet Turan Erozan; Michael Hefenbrock; Michael Beigl; Jasmin Aghassi-Hagmann; Mehdi Baradaran Tahoori (IEEE Trans. Inf. Forensics Secur., 2020)

Detecting Episodes of Increased Cough Using Kinetic Earables. - Tobias Röddiger; Michael Beigl; Michael Hefenbrock; Daniel Wolffram; Erik Pescara (AHs, 2021)

Printed Stochastic Computing Neural Networks. - Dennis D. Weller; Nathaniel Bleier; Michael Hefenbrock; Jasmin Aghassi-Hagmann; Michael Beigl; Rakesh Kumar 002; Mehdi B. Tahoori (DATE, 2021)

NeuroScrub: Mitigating Retention Failures Using Approximate Scrubbing in Neuromorphic Fabric Based on Resistive Memories. - Soyed Tuhin Ahmed; Michael Hefenbrock; Christopher Münch; Mehdi B. Tahoori (ETS, 2021)

In-situ Tuning of Printed Neural Networks for Variation Tolerance. - Michael Hefenbrock; Dennis D. Weller; Jasmin Aghassi-Hagmann; Michael Beigl; Mehdi B. Tahoori (DATE, 2022)

Process and Runtime Variation Robustness for Spintronic-Based Neuromorphic Fabric. - Soyed Tuhin Ahmed; Mahta Mayahinia; Michael Hefenbrock; Christopher Münch; Mehdi B. Tahoori (ETS, 2022)

Aging-Aware Training for Printed Neuromorphic Circuits. - Haibin Zhao; Michael Hefenbrock; Michael Beigl; Mehdi B. Tahoori (ICCAD, 2022)

Universal Distributional Decision-Based Black-Box Adversarial Attack with Reinforcement Learning. - Yiran Huang; Yexu Zhou; Michael Hefenbrock; Till Riedel; Likun Fang; Michael Beigl (ICONIP (3), 2022)

Improving Human Activity Recognition Models by Learnable Sparse Wavelet Layer. - Haibin Zhao; Yexu Zhou; Till Riedel; Michael Hefenbrock; Michael Beigl (ISWC, 2022)

TinyHAR: A Lightweight Deep Learning Model Designed for Human Activity Recognition. - Yexu Zhou; Haibin Zhao; Yiran Huang; Till Riedel; Michael Hefenbrock; Michael Beigl (ISWC, 2022)

Automatic Feature Engineering Through Monte Carlo Tree Search. - Yiran Huang; Yexu Zhou; Michael Hefenbrock; Till Riedel; Likun Fang; Michael Beigl (ECML/PKDD (3), 2022)

Counterfeit Detection and Prevention in Additive Manufacturing Based on Unique Identification of Optical Fingerprints of Printed Structures. - Ahmet Turan Erozan; Michael Hefenbrock; Dennis R. E. Gnad; Michael Beigl; Jasmin Aghassi-Hagmann; Mehdi B. Tahoori (IEEE Access, 2022)

McXai: Local model-agnostic explanation as two games. - Yiran Huang; Nicole Schaal; Michael Hefenbrock; Yexu Zhou; Till Riedel; Likun Fang; Michael Beigl (CoRR, 2022)

Fast and Efficient High-Sigma Yield Analysis and Optimization Using Kernel Density Estimation on a Bayesian Optimized Failure Rate Model. - Dennis D. Weller; Michael Hefenbrock; Michael Beigl; Mehdi B. Tahoori (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022)

Modelling and Training Printed Neuromorphic Circuits - Michael Hefenbrock (2022)

Automatic Test Pattern Generation and Compaction for Deep Neural Networks. - Dina A. Moussa; Michael Hefenbrock; Christopher Münch; Mehdi B. Tahoori (ASP-DAC, 2023)

Scalable Spintronics-based Bayesian Neural Network for Uncertainty Estimation. - Soyed Tuhin Ahmed; Kamal Danouchi; Michael Hefenbrock; Guillaume Prenat; Lorena Anghel; Mehdi B. Tahoori (DATE, 2023)

Compact Test Pattern Generation For Multiple Faults In Deep Neural Networks. - Dina A. Moussa; Michael Hefenbrock; Mehdi B. Tahoori (DATE, 2023)

Split Additive Manufacturing for Printed Neuromorphic Circuits. - Haibin Zhao; Michael Hefenbrock; Michael Beigl; Mehdi B. Tahoori (DATE, 2023)

Highly-Bespoke Robust Printed Neuromorphic Circuits. - Haibin Zhao; Brojogopal Sapui; Michael Hefenbrock; Zhidong Yang; Michael Beigl; Mehdi B. Tahoori (DATE, 2023)

Remote Identification of Neural Network FPGA Accelerators by Power Fingerprints. - Vincent Meyers; Michael Hefenbrock; Dennis Gnad; Mehdi Baradaran Tahoori (FPL, 2023)

Power-Aware Training for Energy-Efficient Printed Neuromorphic Circuits. - Haibin Zhao; Priyanjana Pal; Michael Hefenbrock; Michael Beigl; Mehdi B. Tahoori (ICCAD, 2023)

McXai: Local Model-Agnostic Explanation As Two Games. - Yiran Huang; Nicole Schaal; Michael Hefenbrock; Yexu Zhou; Till Riedel; Michael Beigl (IJCNN, 2023)

Towards Temporal Information Processing - Printed Neuromorphic Circuits with Learnable Filters. - Haibin Zhao; Priyanjana Pal; Michael Hefenbrock; Michael Beigl; Mehdi Baradaran Tahoori (NANOARCH, 2023)

Spatial-SpinDrop: Spatial Dropout-based Binary Bayesian Neural Network with Spintronics Implementation. - Soyed Tuhin Ahmed; Kamal Danouchi; Michael Hefenbrock; Guillaume Prenat; Lorena Anghel; Mehdi B. Tahoori (CoRR, 2023)

New Horizons in Parameter Regularization: A Constraint Approach. - Jörg K. H. Franke; Michael Hefenbrock; Gregor Köhler; Frank Hutter (CoRR, 2023)

Scale-Dropout: Estimating Uncertainty in Deep Neural Networks Using Stochastic Scale. - Soyed Tuhin Ahmed; Kamal Danouchi; Michael Hefenbrock; Guillaume Prenat; Lorena Anghel; Mehdi B. Tahoori (CoRR, 2023)

NeuroScrub+: Mitigating Retention Faults Using Flexible Approximate Scrubbing in Neuromorphic Fabric Based on Resistive Memories. - Soyed Tuhin Ahmed; Michael Hefenbrock; Christopher Münch; Mehdi B. Tahoori (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

SpinBayes: Algorithm-Hardware Co-Design for Uncertainty Estimation Using Bayesian In-Memory Approximation on Spintronic-Based Architectures. - Soyed Tuhin Ahmed; Kamal Danouchi; Michael Hefenbrock; Guillaume Prenat; Lorena Anghel; Mehdi B. Tahoori (ACM Trans. Embed. Comput. Syst., 2023)

Embedding Hardware Approximations in Discrete Genetic-Based Training for Printed MLPs. - Florentia Afentaki; Michael Hefenbrock; Georgios Zervakis 001; Mehdi B. Tahoori (DATE, 2024)

Analog Printed Spiking Neuromorphic Circuit. - Priyanjana Pal; Haibin Zhao; Maha Shatta; Michael Hefenbrock; Sina Bakhtavari Mamaghani; Sani R. Nassif; Michael Beigl; Mehdi B. Tahoori (DATE, 2024)

Testing Spintronics Implemented Monte Carlo Dropout-Based Bayesian Neural Networks. - Soyed Tuhin Ahmed; Kamal Danouchi; Michael Hefenbrock; Guillaume Prenat; Lorena Anghel; Mehdi B. Tahoori (ETS, 2024)

Fault Sensitivity Analysis of Printed Bespoke Multilayer Perceptron Classifiers. - Priyanjana Pal; Florentia Afentaki; Haibin Zhao; Gurol Saglam; Michael Hefenbrock; Georgios Zervakis 001; Michael Beigl; Mehdi B. Tahoori (ETS, 2024)

Trained to Leak: Hiding Trojan Side-Channels in Neural Network Weights. - Vincent Meyers; Michael Hefenbrock; Dennis Gnad; Mehdi B. Tahoori (HOST, 2024)

Tiny Deep Ensemble: Uncertainty Estimation in Edge AI Accelerators via Ensembling Normalization Layers with Shared Weights. - Soyed Tuhin Ahmed; Michael Hefenbrock; Mehdi B. Tahoori (ICCAD, 2024)

Neural Architecture Search for Highly Bespoke Robust Printed Neuromorphic Circuits. - Priyanjana Pal; Haibin Zhao; Tara Gheshlaghi; Michael Hefenbrock; Michael Beigl; Mehdi B. Tahoori (ICCAD, 2024)

Deep Neural Network Pruning with Progressive Regularizer. - Yexu Zhou; Haibin Zhao; Michael Hefenbrock; Siyan Li; Yiran Huang; Michael Beigl (IJCNN, 2024)

Improving Deep Learning Optimization through Constrained Parameter Regularization. - Jörg K. H. Franke; Michael Hefenbrock; Gregor Köhler; Frank Hutter (NeurIPS, 2024)

Testing Spintronics Implemented Monte Carlo Dropout-Based Bayesian Neural Networks. - Soyed Tuhin Ahmed; Michael Hefenbrock; Guillaume Prenat; Lorena Anghel; Mehdi B. Tahoori (CoRR, 2024)

Design-time Reference Current Generation for Robust Spintronic-based Neuromorphic Architecture. - Soyed Tuhin Ahmed; Mahta Mayahinia; Michael Hefenbrock; Christopher Münch; Mehdi B. Tahoori (ACM J. Emerg. Technol. Comput. Syst., 2024)

Testing for Multiple Faults in Deep Neural Networks. - Dina A. Moussa; Michael Hefenbrock; Mehdi B. Tahoori (IEEE Des. Test, 2024)

Towards Functional Safety of Neural Network Hardware Accelerators: Concurrent Out-of-Distribution Detection in Hardware Using Power Side-Channel Analysis. - Vincent Meyers; Michael Hefenbrock; Mahboobe Sadeghipourrudsari; Dennis Gnad; Mehdi B. Tahoori (ASP-DAC, 2025)

ADAPT-pNC: Mitigating Device Variability and Sensor Noise in Printed Neuromorphic Circuits with SO Adaptive Learnable Filters. - Tara Gheshlaghi; Priyanjana Pal; Haibin Zhao; Michael Hefenbrock; Michael Beigl; Mehdi B. Tahoori (DATE, 2025)

Automatic Test Pattern Generation for Printed Neuromorphic Circuits. - Tara Gheshlaghi; Priyanjana Pal; Alexander Studt; Michael Hefenbrock; Michael Beigl; Mehdi B. Tahoori (ETS, 2025)

Leveraging Neural Trojan Side-Channels for Output Exfiltration. - Vincent Meyers; Michael Hefenbrock; Dennis Gnad; Mehdi B. Tahoori (Cryptogr., 2025)

Compressed Test Pattern Generation for Deep Neural Networks. - Dina A. Moussa; Michael Hefenbrock; Mehdi B. Tahoori (IEEE Trans. Computers, 2025)

Learning in Compact Spaces with Approximately Normalized Transformers. - Jörg K. H. Franke; Urs Spiegelhalter; Marianna Nezhurina; Jenia Jitsev; Frank Hutter; Michael Hefenbrock (CoRR, 2025)

Neural Evolutionary Architecture Search for Compact Printed Analog Neuromorphic Circuits. - Haibin Zhao; Priyanjana Pal; Michael Hefenbrock; Yuhong Wang; Michael Beigl; Mehdi B. Tahoori (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2025)