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Benjamin Scellier
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A deep learning framework for neuroscience
BA Richards, TP Lillicrap, P Beaudoin, Y Bengio, R Bogacz, ...
Nature neuroscience 22 (11), 1761-1770, 2019
8542019
Equilibrium propagation: bridging the gap between energy-based models and backpropagation
B Scellier, Y Bengio
Frontiers in computational neuroscience 11, 24, 2017
4912017
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
752020
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
652021
Equivalence of equilibrium propagation and recurrent backpropagation
B Scellier, Y Bengio
Neural computation 31 (2), 312-329, 2019
472019
Generalization of Equilibrium Propagation to Vector Field Dynamics
B Scellier, A Goyal, J Binas, T Mesnard, Y Bengio
arXiv preprint arXiv:1808.04873, 2018
45*2018
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
422019
Equilibrium Propagation with Continual Weight Updates
M Ernoult, J Grollier, D Querlioz, Y Bengio, B Scellier
arXiv preprint arXiv:2005.04168, 2020
342020
A deep learning theory for neural networks grounded in physics
B Scellier
arXiv preprint arXiv:2103.09985, 2021
222021
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
212016
Learning by non-interfering feedback chemical signaling in physical networks
VR Anisetti, B Scellier, JM Schwarz
Physical Review Research 5 (2), 023024, 2023
92023
Agnostic Physics-Driven Deep Learning
B Scellier, S Mishra, Y Bengio, Y Ollivier
arXiv preprint arXiv:2205.15021, 2022
72022
Energy-based learning algorithms for analog computing: a comparative study
B Scellier, M Ernoult, J Kendall, S Kumar
Thirty-seventh Conference on Neural Information Processing Systems, 2023
6*2023
Frequency propagation: Multi-mechanism learning in nonlinear physical networks
VR Anisetti, A Kandala, B Scellier, JM Schwarz
arXiv preprint arXiv:2208.08862, 2022
62022
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
62022
Contrastive learning through non-equilibrium memory
M Falk, A Strupp, B Scellier, A Murugan
arXiv preprint arXiv:2312.17723, 2023
12023
A universal approximation theorem for nonlinear resistive networks
B Scellier, S Mishra
arXiv preprint arXiv:2312.15063, 2023
12023
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