| Backpropagation-based learning techniques for deep spiking neural networks: A survey M Dampfhoffer, T Mesquida, A Valentian, L Anghel IEEE Transactions on Neural Networks and Learning Systems, 2023 | 60 | 2023 |
| Are SNNs really more energy-efficient than ANNs? An in-depth hardware-aware study M Dampfhoffer, T Mesquida, A Valentian, L Anghel IEEE Transactions on Emerging Topics in Computational Intelligence 7 (3 …, 2022 | 55 | 2022 |
| Investigating current-based and gating approaches for accurate and energy-efficient spiking recurrent neural networks M Dampfhoffer, T Mesquida, A Valentian, L Anghel International Conference on Artificial Neural Networks, 359-370, 2022 | 21 | 2022 |
| 1S1R optimization for high‐frequency inference on binarized spiking neural networks J Minguet Lopez, Q Rafhay, M Dampfhoffer, L Reganaz, N Castellani, ... Advanced Electronic Materials 8 (8), 2200323, 2022 | 12 | 2022 |
| Improving the robustness of neural networks to noisy multi-level non-volatile memory-based synapses M Dampfhoffer, JM Lopez, T Mesquida, A Valentian, L Anghel 2023 International Joint Conference on Neural Networks (IJCNN), 1-8, 2023 | 9 | 2023 |
| Leveraging sparsity with spiking recurrent neural networks for energy-efficient keyword spotting M Dampfhoffer, T Mesquida, E Hardy, A Valentian, L Anghel ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 8 | 2023 |
| OxRAM+ OTS optimization for binarized neural network hardware implementation JM Lopez, T Hirtzlin, M Dampfhoffer, L Grenouillet, L Reganaz, G Navarro, ... Semiconductor Science and Technology 37 (1), 014001, 2021 | 7 | 2021 |
| Neuromorphic lip-reading with signed spiking gated recurrent units M Dampfhoffer, T Mesquida Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 4 | 2024 |
| G2N2: Lightweight event stream classification with GRU graph neural networks T Mesquida, M Dampfhoffer, T Dalgaty, P Vivet, A Sironi, C Posch BMVC 2023-The 34th British Machine Vision Conference, 660, 2023 | 2 | 2023 |
| Models and algorithms for implementing energy-efficient spiking neural networks on neuromorphic hardware at the edge M Dampfhoffer Université Grenoble Alpes [2020-....], 2023 | 1 | 2023 |
| 1S1R Multi-Level-Cell for Dense Quantized Recurrent Spiking Neural Network Inference Computing JM Lopez, M Dampfhoffer, G Navarro, M Bernard, C Carabasse, ... ssdm 2024, 2024 | | 2024 |
| 1S1R sub-threshold operation in Crossbar Arrays for Neural Networks hardware implementation JM Lopez, M Dampfhoffer, T Hirtzlin, L Reganaz, L Grenouillet, G Navarro, ... 2023 30th International Conference on Mixed Design of Integrated Circuits …, 2023 | | 2023 |
| Modèles et algorithmes pour l'implémentation de réseaux de neurones impulsionnels à faible consommation énergétique sur du matériel neuromorphique M Dampfhoffer Université Grenoble Alpes, 2023 | | 2023 |
| 7DEOH RI &RQWHQWV JM Lopez, M Dampfhoffer, T Hirtzlin, L Reganaz, L Grenouillet, G Navarro, ... | | |
