| Towards 10000TOPS/W DNN inference with analog in-memory computing–a circuit blueprint, device options and requirements S Cosemans, B Verhoef, J Doevenspeck, IA Papistas, F Catthoor, ... 2019 IEEE International Electron Devices Meeting (IEDM), 22.2. 1-22.2. 4, 2019 | 68 | 2019 |
| SOT-MRAM based analog in-memory computing for DNN inference J Doevenspeck, K Garello, B Verhoef, R Degraeve, S Van Beek, D Crotti, ... 2020 IEEE Symposium on VLSI Technology, 1-2, 2020 | 64 | 2020 |
| DIANA: An end-to-end energy-efficient digital and ANAlog hybrid neural network SoC K Ueyoshi, IA Papistas, P Houshmand, GM Sarda, V Jain, M Shi, Q Zheng, ... 2022 IEEE International Solid-State Circuits Conference (ISSCC) 65, 1-3, 2022 | 57 | 2022 |
| A 22 nm, 1540 TOP/s/W, 12.1 TOP/s/mm2 in-Memory Analog Matrix-Vector-Multiplier for DNN Acceleration IA Papistas, S Cosemans, B Rooseleer, J Doevenspeck, MH Na, A Mallik, ... 2021 IEEE Custom Integrated Circuits Conference (CICC), 1-2, 2021 | 42 | 2021 |
| Chain of magnetic tunnel junctions as a spintronic memristor E Raymenants, A Vaysset, D Wan, M Manfrini, O Zografos, O Bultynck, ... Journal of Applied Physics 124 (15), 2018 | 21 | 2018 |
| Multi-pillar SOT-MRAM for accurate analog in-memory DNN inference J Doevenspeck, K Garello, S Rao, F Yasin, S Couet, G Jayakumar, ... 2021 Symposium on VLSI Technology, 1-2, 2021 | 19 | 2021 |
| IGZO-based compute cell for analog in-memory computing—DTCO analysis to enable ultralow-power AI at edge D Saito, J Doevenspeck, S Cosemans, H Oh, M Perumkunnil, IA Papistas, ... IEEE Transactions on Electron Devices 67 (11), 4616-4620, 2020 | 19 | 2020 |
| OxRRAM-based analog in-memory computing for deep neural network inference: A conductance variability study J Doevenspeck, R Degraeve, A Fantini, S Cosemans, A Mallik, ... IEEE Transactions on Electron Devices 68 (5), 2301-2305, 2021 | 10 | 2021 |
| Temporal sequence learning with a history-sensitive probabilistic learning rule intrinsic to oxygen vacancy-based RRAM J Doevenspeck, R Degraeve, A Fantini, P Debacker, D Verkest, ... 2018 IEEE International Electron Devices Meeting (IEDM), 20.5. 1-20.5. 4, 2018 | 7 | 2018 |
| Dynamic quantization range control for analog-in-memory neural networks acceleration N Laubeuf, J Doevenspeck, IA Papistas, M Caselli, S Cosemans, ... ACM Transactions on Design Automation of Electronic Systems (TODAES) 27 (5 …, 2022 | 6 | 2022 |
| Noise tolerant ternary weight deep neural networks for analog in-memory inference J Doevenspeck, P Vrancx, N Laubeuf, A Mallik, P Debacker, D Verkest, ... 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 5 | 2021 |
| Analytic variability study of inference accuracy in RRAM arrays with a binary tree winner-take-all circuit for neuromorphic applications J Doevenspeck, R Degraeve, S Cosemans, P Roussel, BE Verhoef, ... 2018 48th European Solid-State Device Research Conference (ESSDERC), 62-65, 2018 | 5 | 2018 |
| Design and simulation of plasmonic interference-based majority gate J Doevenspeck, O Zografos, S Gurunarayanan, R Lauwereins, ... AIP Advances 7 (6), 2017 | 5 | 2017 |
| Neural network learning using non-ideal resistive memory devices Y Kim, T Gokmen, H Miyazoe, P Solomon, S Kim, A Ray, J Doevenspeck, ... Frontiers in Nanotechnology 4, 1008266, 2022 | 4 | 2022 |
| Opportunities and challenges of resistive RAM for neuromorphic applications R Degraeve, A Mallik, D Garbin, J Doevenspeck, A Fantini, D Rodopoulos, ... 2018 IEEE International Symposium on the Physical and Failure Analysis of …, 2018 | 3 | 2018 |
| Low voltage transient RESET kinetic modeling of OxRRAM for neuromorphic applications J Doevenspeck, R Degraeve, A Fantini, P Debacker, D Verkest, ... 2019 IEEE International Reliability Physics Symposium (IRPS), 1-6, 2019 | 2 | 2019 |
| In-memory neural network computing with resistive memories J Doevenspeck KU Leuven, 2021 | 1 | 2021 |
| Novel memory devices tailored to analog in-memory computing for neural network inference S Cosemans, J Doevenspeck, B Verhoef, I Papistas, N Laubeuf, ... | 1 | 2020 |
| Modeling and demonstration of oxygen vacancy-based RRAM as probabilistic device for sequence learning J Doevenspeck, R Degraeve, A Fantini, P Debacker, D Verkest, ... IEEE Transactions on Electron Devices 67 (2), 505-511, 2019 | 1 | 2019 |
| Gait identification using stochastic OXRRAM-based time sequence machine learning R Degraeve, J Doevenspeck, A Fantini, P Debacker, D Linten, D Verkest 2019 Symposium on VLSI Technology, T84-T85, 2019 | 1 | 2019 |
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