Fault Tolerance on Control Applications: Empirical Investigations of Impacts from Incorrect Calculations. - Mikail Yayla; Kuan-Hsun Chen; Jian-Jia Chen (EITEC@CPSWeek, 2018)

Resource-Efficient Nanoparticle Classification Using Frequency Domain Analysis. - Mikail Yayla; Anas Toma; Jan Eric Lenssen; Victoria Shpacovitch; Kuan-Hsun Chen; Frank Weichert; Jian-Jia Chen (Bildverarbeitung für die Medizin, 2019)

Nanoparticle Classification Using Frequency Domain Analysis on Resource-Limited Platforms. - Mikail Yayla; Anas Toma; Kuan-Hsun Chen; Jan Eric Lenssen; Victoria Shpacovitch; Roland Hergenröder; Frank Weichert; Jian-Jia Chen (Sensors, 2019)

Software-Based Memory Analysis Environments for In-Memory Wear-Leveling. - Christian Hakert; Kuan-Hsun Chen; Mikail Yayla; Georg von der Brüggen; Sebastian Blömeke; Jian-Jia Chen (ASP-DAC, 2020)

Towards Explainable Bit Error Tolerance of Resistive RAM-Based Binarized Neural Networks. - Sebastian Buschjäger; Jian-Jia Chen; Kuan-Hsun Chen; Mario Günzel; Christian Hakert; Katharina Morik; Rodion Novkin; Lukas Pfahler; Mikail Yayla (CoRR, 2020)

Margin-Maximization in Binarized Neural Networks for Optimizing Bit Error Tolerance. - Sebastian Buschjäger; Jian-Jia Chen; Kuan-Hsun Chen; Mario Günzel; Christian Hakert; Katharina Morik; Rodion Novkin; Lukas Pfahler; Mikail Yayla (DATE, 2021)

FeFET and NCFET for Future Neural Networks: Visions and Opportunities. - Mikail Yayla; Kuan-Hsun Chen; Georgios Zervakis 001; Jörg Henkel; Jian-Jia Chen; Hussam Amrouch (DATE, 2021)

Brain-Inspired Computing: Adventure from Beyond CMOS Technologies to Beyond von Neumann Architectures ICCAD Special Session Paper. - Hussam Amrouch; Jian-Jia Chen; Kaushik Roy 001; Yuan Xie 001; Indranil Chakraborty; Wenqin Huangfu; Ling Liang; Fengbin Tu; Cheng Wang 036; Mikail Yayla (ICCAD, 2021)

Binarized SNNs: Efficient and Error-Resilient Spiking Neural Networks through Binarization. - Ming-Liang Wei; Mikail Yayla; Shu-Yin Ho; Jian-Jia Chen; Chia-Lin Yang; Hussam Amrouch (ICCAD, 2021)

Bit Error Tolerance Metrics for Binarized Neural Networks. - Sebastian Buschjäger; Jian-Jia Chen; Kuan-Hsun Chen; Mario Günzel; Katharina Morik; Rodion Novkin; Lukas Pfahler; Mikail Yayla (CoRR, 2021)

Universal Approximation Theorems of Fully Connected Binarized Neural Networks. - Mikail Yayla; Mario Günzel; Burim Ramosaj; Jian-Jia Chen (CoRR, 2021)

Machine Learning Based on Emerging Memories. - Mikail Yayla; Sebastian Buschjäger; Hussam Amrouch (Mach. Learn. under Resour. Constraints Vol. 1 (1), 2022)

Memory-efficient training of binarized neural networks on the edge. - Mikail Yayla; Jian-Jia Chen (DAC, 2022)

TREAM: A Tool for Evaluating Error Resilience of Tree-Based Models Using Approximate Memory. - Mikail Yayla; Zahra Valipour Dehnoo; Mojtaba Masoudinejad; Jian-Jia Chen (SAMOS, 2022)

FeFET-Based Binarized Neural Networks Under Temperature-Dependent Bit Errors. - Mikail Yayla; Sebastian Buschjäger; Aniket Gupta; Jian-Jia Chen; Jörg Henkel; Katharina Morik; Kuan-Hsun Chen; Hussam Amrouch (IEEE Trans. Computers, 2022)

Reliable Binarized Neural Networks on Unreliable Beyond Von-Neumann Architecture. - Mikail Yayla; Simon Thomann; Sebastian Buschjäger; Katharina Morik; Jian-Jia Chen; Hussam Amrouch (IEEE Trans. Circuits Syst. I Regul. Pap., 2022)

Robust and Tiny Binary Neural Networks using Gradient-based Explainability Methods. - Muhammad Sabih; Mikail Yayla; Frank Hannig; Jürgen Teich; Jian-Jia Chen (EuroMLSys@EuroSys, 2023)

Temperature-Aware Memory Mapping and Active Cooling of Neural Processing Units. - Vahidreza Moghaddas; Hammam Kattan; Tim Bücher; Mikail Yayla; Jian-Jia Chen; Hussam Amrouch (ISLPED, 2023)

DAEBI: A Tool for Data Flow and Architecture Explorations of Binary Neural Network Accelerators. - Mikail Yayla; Cecilia Latotzke; Robert Huber; Somar Iskif; Tobias Gemmeke; Jian-Jia Chen (SAMOS, 2023)

Reliable Brain-inspired AI Accelerators using Classical and Emerging Memories. - Mikail Yayla; Simon Thomann; Md. Mazharul Islam 006; Ming-Liang Wei; Shu-Yin Ho; Ahmedullah Aziz; Chia-Lin Yang; Jian-Jia Chen; Hussam Amrouch (VTS, 2023)

HEP-BNN: A Framework for Finding Low-Latency Execution Configurations of BNNs on Heterogeneous Multiprocessor Platforms. - Leonard David Bereholschi; Ching-Chi Lin; Mikail Yayla; Jian-Jia Chen (CoRR, 2023)

HW/SW Codesign for Robust and Efficient Binarized SNNs by Capacitor Minimization. - Mikail Yayla; Simon Thomann; Ming-Liang Wei; Chia-Lin Yang; Jian-Jia Chen; Hussam Amrouch (CoRR, 2023)

HW/SW Codesign for Approximation-Aware Binary Neural Networks. - Abhilasha Dave; Fabio Frustaci; Fanny Spagnolo; Mikail Yayla; Jian-Jia Chen; Hussam Amrouch (IEEE J. Emerg. Sel. Topics Circuits Syst., 2023)

Impact of Non-Volatile Memory Cells on Spiking Neural Network Annealing Machine With In-Situ Synapse Processing. - Ming-Liang Wei; Mikail Yayla; Shu-Yin Ho; Jian-Jia Chen; Hussam Amrouch; Chia-Lin Yang (IEEE Trans. Circuits Syst. I Regul. Pap., 2023)

Unlocking Efficiency in BNNs: Global by Local Thresholding for Analog-Based HW Accelerators. - Mikail Yayla; Fabio Frustaci; Fanny Spagnolo; Jian-Jia Chen; Hussam Amrouch (IEEE J. Emerg. Sel. Topics Circuits Syst., 2023)

Evaluating the Impact of Racetrack Memory Misalignment Faults on BNNs Performance. - Leonard David Bereholschi; Mikail Yayla; Jian-Jia Chen; Kuan-Hsun Chen; Asif Ali Khan (SAMOS, 2024)

EdgeVision SoC: PPA-Impact of RTL-level Modifications. - Mikail Yayla; Clifford Leon Dmello; Georg Ellguth; Uwe Steeb; Tim Leuchter; Marcus Pietzsch; Holger Eisenreich (SOCC, 2024)