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ORCIDJonas Doevenspeck
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2020 – today
- 2024
[c6]Pascal Alexander Hager, Bert Moons, Stefan Cosemans, Ioannis A. Papistas, Bram Rooseleer, Jeroen Van Loon, Roel Uytterhoeven, Florian Zaruba, Spyridoula Koumousi, Milos Stanisavljevic, Stefan Mach, Sebastiaan Mutsaards, Riduan Khaddam Aljameh, Gua Hao Khov, Brecht Machiels, Cristian Olar, Anastasios Psarras, Sander Geursen, Jeroen Vermeeren, Yi Lu, Abhishek Maringanti, Deepak Ameta, Leonidas Katselas, Noah Hütter, Manuel Schmuck, Swetha Sivadas, Karishma Sharma, Manuel Oliveira, Ramon Aerne, Nitish Sharma, Timir Soni, Beatrice Bussolino, Djordje Pesut, Michele Pallaro, Andrei Podlesnii, Alexios Lyrakis, Yannick Ruffiner, Martino Dazzi, Johannes Thiele, Koen Goetschalckx, Nazareno Bruschi, Jonas Doevenspeck, Bram Verhoef, Stefan Linz, Giuseppe Garcea, Jonathan Ferguson, Ioannis Koltsidas, Evangelos Eleftheriou:
11.3 Metis AIPU: A 12nm 15TOPS/W 209.6TOPS SoC for Cost- and Energy-Efficient Inference at the Edge. ISSCC 2024: 212-214- 2022
- [j1]Nathan Laubeuf
, Jonas Doevenspeck, Ioannis A. Papistas, Michele Caselli, Stefan Cosemans, Peter Vrancx, Debjyoti Bhattacharjee, Arindam Mallik, Peter Debacker, Diederik Verkest, Francky Catthoor, Rudy Lauwereins:
Dynamic Quantization Range Control for Analog-in-Memory Neural Networks Acceleration. ACM Trans. Design Autom. Electr. Syst. 27(5): 46:1-46:21 (2022) - [c5]Kodai Ueyoshi, Ioannis A. Papistas, Pouya Houshmand, Giuseppe Maria Sarda, Vikram Jain, Man Shi, Qilin Zheng, Juan Sebastian Piedrahita Giraldo, Peter Vrancx, Jonas Doevenspeck, Debjyoti Bhattacharjee, Stefan Cosemans, Arindam Mallik, Peter Debacker, Diederik Verkest, Marian Verhelst:
DIANA: An End-to-End Energy-Efficient Digital and ANAlog Hybrid Neural Network SoC. ISSCC 2022: 1-3 - 2021
- [c4]Ioannis A. Papistas, Stefan Cosemans, Bram Rooseleer, Jonas Doevenspeck, Myung Hee Na, Arindam Mallik, Peter Debacker, Diederik Verkest:
A 22 nm, 1540 TOP/s/W, 12.1 TOP/s/mm2 in-Memory Analog Matrix-Vector-Multiplier for DNN Acceleration. CICC 2021: 1-2 - [c3]Jonas Doevenspeck, Peter Vrancx, Nathan Laubeuf, Arindam Mallik, Peter Debacker, Diederik Verkest, Rudy Lauwereins, Wim Dehaene:
Noise tolerant ternary weight deep neural networks for analog in-memory inference. IJCNN 2021: 1-8
2010 – 2019
- 2019
- [c2]Jonas Doevenspeck, Robin Degraeve, Andrea Fantini, Peter Debacker, Diederik Verkest, Rudy Lauwereins, Wim Dehaene:
Low Voltage Transient RESET Kinetic Modeling of OxRRAM for Neuromorphic Applications. IRPS 2019: 1-6 - 2018
- [c1]Jonas Doevenspeck, Robin Degraeve, Stefan Cosemans, Philippe Roussel, Bram-Ernst Verhoef, Rudy Lauwereins, Wim Dehaene:
Analytic variability study of inference accuracy in RRAM arrays with a binary tree winner-take-all circuit for neuromorphic applications. ESSDERC 2018: 62-65
Coauthor Index
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