| A deep learning framework for neuroscience BA Richards, TP Lillicrap, P Beaudoin, Y Bengio, R Bogacz, ... Nature neuroscience 22 (11), 1761-1770, 2019 | 1222 | 2019 |
| Equilibrium propagation: bridging the gap between energy-based models and backpropagation B Scellier, Y Bengio Frontiers in computational neuroscience 11, 24, 2017 | 763 | 2017 |
| Training End-to-End Analog Neural Networks with Equilibrium Propagation J Kendall, R Pantone, K Manickavasagam, Y Bengio, B Scellier arXiv preprint arXiv:2006.01981, 2020 | 128 | 2020 |
| Scaling equilibrium propagation to deep convnets by drastically reducing its gradient estimator bias A Laborieux, M Ernoult, B Scellier, Y Bengio, J Grollier, D Querlioz Frontiers in neuroscience 15, 633674, 2021 | 114 | 2021 |
| Training of physical neural networks A Momeni, B Rahmani, B Scellier, LG Wright, PL McMahon, CC Wanjura, ... Nature 645 (8079), 53-61, 2025 | 81 | 2025 |
| Updates of equilibrium prop match gradients of backprop through time in an rnn with static input M Ernoult, J Grollier, D Querlioz, Y Bengio, B Scellier Advances in Neural Information Processing Systems 32, 7081-7091, 2019 | 67 | 2019 |
| Equivalence of equilibrium propagation and recurrent backpropagation B Scellier, Y Bengio Neural computation 31 (2), 312-329, 2019 | 64 | 2019 |
| Equilibrium Propagation with Continual Weight Updates M Ernoult, J Grollier, D Querlioz, Y Bengio, B Scellier arXiv preprint arXiv:2005.04168, 2020 | 55 | 2020 |
| Energy-based learning algorithms for analog computing: a comparative study B Scellier, M Ernoult, J Kendall, S Kumar Advances in Neural Information Processing Systems 36, 2024 | 52 | 2024 |
| Generalization of Equilibrium Propagation to Vector Field Dynamics B Scellier, A Goyal, J Binas, T Mesnard, Y Bengio arXiv preprint arXiv:1808.04873, 2018 | 48 | 2018 |
| A deep learning theory for neural networks grounded in physics B Scellier arXiv preprint arXiv:2103.09985, 2021 | 38 | 2021 |
| Learning by non-interfering feedback chemical signaling in physical networks VR Anisetti, B Scellier, JM Schwarz Physical Review Research 5 (2), 023024, 2023 | 29 | 2023 |
| Frequency propagation: Multimechanism learning in nonlinear physical networks VR Anisetti, A Kandala, B Scellier, JM Schwarz Neural Computation 36 (4), 596-620, 2024 | 25 | 2024 |
| Feedforward initialization for fast inference of deep generative networks is biologically plausible Y Bengio, B Scellier, O Bilaniuk, J Sacramento, W Senn arXiv preprint arXiv:1606.01651, 2016 | 25 | 2016 |
| Agnostic Physics-Driven Deep Learning B Scellier, S Mishra, Y Bengio, Y Ollivier arXiv preprint arXiv:2205.15021, 2022 | 19 | 2022 |
| Temporal Contrastive Learning through implicit non-equilibrium memory MJ Falk, AT Strupp, B Scellier, A Murugan Nature Communications 16 (1), 2163, 2025 | 14 | 2025 |
| A Fast Algorithm to Simulate Nonlinear Resistive Networks B Scellier arXiv preprint arXiv:2402.11674, 2024 | 13 | 2024 |
| Vacua of ω-deformed SO (8) supergravity D Berman, T Fischbacher, G Inverso, B Scellier Journal of High Energy Physics 2022 (6), 1-47, 2022 | 13 | 2022 |
| Quantum Equilibrium Propagation: Gradient-Descent Training of Quantum Systems B Scellier arXiv preprint arXiv:2406.00879, 2024 | 7 | 2024 |
| Universal approximation theorem for nonlinear resistive networks B Scellier, S Mishra Physical Review Applied 23 (4), 044009, 2025 | 4 | 2025 |
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
