A 0.086-mm C Frenkel, M Lefebvre, JD Legat, D Bol
IEEE Transactions on Biomedical Circuits and Systems 13 (1), 145-158, 2019
428 2019 Hand-gesture recognition based on EMG and event-based camera sensor fusion: A benchmark in neuromorphic computing E Ceolini*, C Frenkel*, SB Shrestha*, G Taverni, L Khacef, M Payvand, ...
Frontiers in Neuroscience 14, 2020
188 2020 MorphIC: A 65-nm 738k-Synapse/mm C Frenkel, JD Legat, D Bol
IEEE Transactions on Biomedical Circuits and Systems 13 (5), 999-1010, 2019
167 2019 Learning without feedback: Fixed random learning signals allow for feedforward training of deep neural networks C Frenkel*, M Lefebvre*, D Bol
Frontiers in neuroscience 15, 2021
118 * 2021 Bottom-up and top-down approaches for the design of neuromorphic processing systems: tradeoffs and synergies between natural and artificial intelligence C Frenkel, D Bol, G Indiveri
Proceedings of the IEEE 111 (6), 623-652, 2023
112 * 2023 ReckOn: A 28nm sub-mm2 task-agnostic spiking recurrent neural network processor enabling on-chip learning over second-long timescales C Frenkel, G Indiveri
2022 IEEE International Solid-State Circuits Conference (ISSCC) 65, 1-3, 2022
97 2022 Spiking neural network integrated circuits: A review of trends and future directions A Basu*, L Deng*, C Frenkel*, X Zhang*
2022 IEEE Custom Integrated Circuits Conference (CICC), 1-8, 2022
85 2022 SleepTalker: A ULV 802.15. 4a IR-UWB transmitter SoC in 28-nm FDSOI achieving 14 pJ/b at 27 Mb/s with channel selection based on adaptive FBB and digitally programmable pulse … G de Streel, F Stas, T Gurne, F Durant, C Frenkel, A Cathelin, D Bol
IEEE Journal of Solid-State Circuits 52 (4), 1163-1177, 2017
77 2017 A 28-nm Convolutional Neuromorphic Processor Enabling Online Learning with Spike-Based Retinas C Frenkel, JD Legat, D Bol
2020 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2020
55 2020 The neurobench framework for benchmarking neuromorphic computing algorithms and systems J Yik, K Van den Berghe, D den Blanken, Y Bouhadjar, M Fabre, ...
Nature Communications 16 (1), 1545, 2025
42 * 2025 PCM-trace: Scalable Synaptic Eligibility Traces with Resistivity Drift of Phase-Change Materials Y Demirağ, F Moro, T Dalgaty, G Navarro, C Frenkel, G Indiveri, ...
2021 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2021
36 2021 SleepRunner: A 28-nm FDSOI ULP Cortex-M0 MCU With ULL SRAM and UFBR PVT Compensation for 2.6–3.6-μ W/DMIPS 40–80-MHz Active Mode and 131-nW … D Bol, M Schramme, L Moreau, P Xu, R Dekimpe, R Saeidi, T Haine, ...
IEEE Journal of Solid-State Circuits 56 (7), 2256-2269, 2021
36 2021 19.6 A 40-to-80MHz Sub-4μw/mhz ULV cortex-M0 MCU SoC in 28nm FDSOI with dual-loop adaptive back-bias generator for 20μs wake-up from deep fully retentive sleep mode D Bol, M Schramme, L Moreau, T Haine, P Xu, C Frenkel, R Dekimpe, ...
2019 IEEE International Solid-State Circuits Conference-(ISSCC), 322-324, 2019
36 2019 A fully-synthesized 20-gate digital spike-based synapse with embedded online learning C Frenkel, G Indiveri, JD Legat, D Bol
2017 IEEE international symposium on circuits and systems (ISCAS), 1-4, 2017
25 2017 Online training of spiking recurrent neural networks with phase-change memory synapses Y Demirag, C Frenkel, M Payvand, G Indiveri
arXiv preprint arXiv:2108.01804, 2021
22 2021 Sparsity provides a competitive advantage C Frenkel
Nature Machine Intelligence 3 (9), 742-743, 2021
19 2021 A compact phenomenological digital neuron implementing the 20 Izhikevich behaviors C Frenkel, JD Legat, D Bol
2017 IEEE Biomedical Circuits and Systems Conference (BioCAS), 1-4, 2017
17 2017 Biologically-inspired training of spiking recurrent neural networks with neuromorphic hardware T Bohnstingl, A Šurina, M Fabre, Y Demirağ, C Frenkel, M Payvand, ...
2022 IEEE 4th International Conference on Artificial Intelligence Circuits …, 2022
12 2022 Stochastic dendrites enable online learning in mixed-signal neuromorphic processing systems M Cartiglia, A Rubino, S Narayanan, C Frenkel, G Haessig, G Indiveri, ...
2022 IEEE International Symposium on Circuits and Systems (ISCAS), 476-480, 2022
12 2022 Bottom-up and top-down neuromorphic processor design: Unveiling roads to embedded cognition C Frenkel
UCLouvain Institute for Information and Communication Technologies …, 2020
11 2020 
David BolECS group, ICTEAM institute, Université catholique de LouvainBestätigte E-Mail-Adresse bei uclouvain.be
