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Mikail Yayla
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2020 – today
- 2023
- [j6]Abhilasha Dave, Fabio Frustaci, Fanny Spagnolo, Mikail Yayla, Jian-Jia Chen, Hussam Amrouch:
HW/SW Codesign for Approximation-Aware Binary Neural Networks. IEEE J. Emerg. Sel. Topics Circuits Syst. 13(1): 33-47 (2023) - [j5]Mikail Yayla, Fabio Frustaci, Fanny Spagnolo, Jian-Jia Chen, Hussam Amrouch:
Unlocking Efficiency in BNNs: Global by Local Thresholding for Analog-Based HW Accelerators. IEEE J. Emerg. Sel. Topics Circuits Syst. 13(4): 940-955 (2023) - [j4]Ming-Liang Wei, Mikail Yayla, Shu-Yin Ho, Jian-Jia Chen, Hussam Amrouch, Chia-Lin Yang:
Impact of Non-Volatile Memory Cells on Spiking Neural Network Annealing Machine With In-Situ Synapse Processing. IEEE Trans. Circuits Syst. I Regul. Pap. 70(11): 4380-4393 (2023) - [c13]Muhammad Sabih, Mikail Yayla, Frank Hannig, Jürgen Teich, Jian-Jia Chen:
Robust and Tiny Binary Neural Networks using Gradient-based Explainability Methods. EuroMLSys@EuroSys 2023: 87-93 - [c12]Vahidreza Moghaddas, Hammam Kattan, Tim Bücher, Mikail Yayla, Jian-Jia Chen, Hussam Amrouch:
Temperature-Aware Memory Mapping and Active Cooling of Neural Processing Units. ISLPED 2023: 1-6 - [c11]Mikail Yayla, Cecilia Latotzke, Robert Huber, Somar Iskif, Tobias Gemmeke, Jian-Jia Chen:
DAEBI: A Tool for Data Flow and Architecture Explorations of Binary Neural Network Accelerators. SAMOS 2023: 107-122 - [c10]Mikail Yayla, Simon Thomann, Md. Mazharul Islam, Ming-Liang Wei, Shu-Yin Ho, Ahmedullah Aziz, Chia-Lin Yang, Jian-Jia Chen, Hussam Amrouch:
Reliable Brain-inspired AI Accelerators using Classical and Emerging Memories. VTS 2023: 1-10 - [i5]Leonard David Bereholschi, Ching-Chi Lin, Mikail Yayla, Jian-Jia Chen:
HEP-BNN: A Framework for Finding Low-Latency Execution Configurations of BNNs on Heterogeneous Multiprocessor Platforms. CoRR abs/2301.05126 (2023) - [i4]Mikail Yayla, Simon Thomann, Ming-Liang Wei, Chia-Lin Yang, Jian-Jia Chen, Hussam Amrouch:
HW/SW Codesign for Robust and Efficient Binarized SNNs by Capacitor Minimization. CoRR abs/2309.02111 (2023) - 2022
- [j3]Mikail Yayla, Sebastian Buschjäger, Aniket Gupta, Jian-Jia Chen, Jörg Henkel, Katharina Morik, Kuan-Hsun Chen, Hussam Amrouch:
FeFET-Based Binarized Neural Networks Under Temperature-Dependent Bit Errors. IEEE Trans. Computers 71(7): 1681-1695 (2022) - [j2]Mikail Yayla, Simon Thomann, Sebastian Buschjäger, Katharina Morik, Jian-Jia Chen, Hussam Amrouch:
Reliable Binarized Neural Networks on Unreliable Beyond Von-Neumann Architecture. IEEE Trans. Circuits Syst. I Regul. Pap. 69(6): 2516-2528 (2022) - [c9]Mikail Yayla, Jian-Jia Chen:
Memory-efficient training of binarized neural networks on the edge. DAC 2022: 661-666 - [c8]Mikail Yayla, Zahra Valipour Dehnoo, Mojtaba Masoudinejad, Jian-Jia Chen:
TREAM: A Tool for Evaluating Error Resilience of Tree-Based Models Using Approximate Memory. SAMOS 2022: 61-73 - [p1]Mikail Yayla, Sebastian Buschjäger, Hussam Amrouch:
Machine Learning Based on Emerging Memories. Mach. Learn. under Resour. Constraints Vol. 1 (1) 2022: 325-337 - 2021
- [c7]Mikail Yayla, Kuan-Hsun Chen, Georgios Zervakis, Jörg Henkel, Jian-Jia Chen, Hussam Amrouch:
FeFET and NCFET for Future Neural Networks: Visions and Opportunities. DATE 2021: 300-305 - [c6]Sebastian Buschjäger, Jian-Jia Chen, Kuan-Hsun Chen, Mario Günzel, Christian Hakert, Katharina Morik, Rodion Novkin, Lukas Pfahler, Mikail Yayla:
Margin-Maximization in Binarized Neural Networks for Optimizing Bit Error Tolerance. DATE 2021: 673-678 - [c5]Hussam Amrouch, Jian-Jia Chen, Kaushik Roy, Yuan Xie, Indranil Chakraborty, Wenqin Huangfu, Ling Liang, Fengbin Tu, Cheng Wang, Mikail Yayla:
Brain-Inspired Computing: Adventure from Beyond CMOS Technologies to Beyond von Neumann Architectures ICCAD Special Session Paper. ICCAD 2021: 1-9 - [c4]Ming-Liang Wei, Mikail Yayla, Shu-Yin Ho, Jian-Jia Chen, Chia-Lin Yang, Hussam Amrouch:
Binarized SNNs: Efficient and Error-Resilient Spiking Neural Networks through Binarization. ICCAD 2021: 1-9 - [i3]Sebastian Buschjäger, Jian-Jia Chen, Kuan-Hsun Chen, Mario Günzel, Katharina Morik, Rodion Novkin, Lukas Pfahler, Mikail Yayla:
Bit Error Tolerance Metrics for Binarized Neural Networks. CoRR abs/2102.01344 (2021) - [i2]Mikail Yayla, Mario Günzel, Burim Ramosaj, Jian-Jia Chen:
Universal Approximation Theorems of Fully Connected Binarized Neural Networks. CoRR abs/2102.02631 (2021) - 2020
- [c3]Christian Hakert, Kuan-Hsun Chen, Mikail Yayla, Georg von der Brüggen, Sebastian Blömeke, Jian-Jia Chen:
Software-Based Memory Analysis Environments for In-Memory Wear-Leveling. ASP-DAC 2020: 651-658 - [i1]Sebastian Buschjäger, Jian-Jia Chen, Kuan-Hsun Chen, Mario Günzel, Christian Hakert, Katharina Morik, Rodion Novkin, Lukas Pfahler, Mikail Yayla:
Towards Explainable Bit Error Tolerance of Resistive RAM-Based Binarized Neural Networks. CoRR abs/2002.00909 (2020)
2010 – 2019
- 2019
- [j1]Mikail Yayla, Anas Toma, Kuan-Hsun Chen, Jan Eric Lenssen, Victoria Shpacovitch, Roland Hergenröder, Frank Weichert, Jian-Jia Chen:
Nanoparticle Classification Using Frequency Domain Analysis on Resource-Limited Platforms. Sensors 19(19): 4138 (2019) - [c2]Mikail Yayla, Anas Toma, Jan Eric Lenssen, Victoria Shpacovitch, Kuan-Hsun Chen, Frank Weichert, Jian-Jia Chen:
Resource-Efficient Nanoparticle Classification Using Frequency Domain Analysis. Bildverarbeitung für die Medizin 2019: 339-344 - 2018
- [c1]Mikail Yayla, Kuan-Hsun Chen, Jian-Jia Chen:
Fault Tolerance on Control Applications: Empirical Investigations of Impacts from Incorrect Calculations. EITEC@CPSWeek 2018: 17-24
Coauthor Index
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