Benjamin Scellier
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Equilibrium propagation: bridging the gap between energy-based models and backpropagation
B Scellier, Y Bengio
Frontiers in computational neuroscience 11, 24, 2017
A deep learning framework for neuroscience
BA Richards, TP Lillicrap, P Beaudoin, Y Bengio, R Bogacz, ...
Nature neuroscience 22 (11), 1761-1770, 2019
Towards a biologically plausible backprop
B Scellier, Y Bengio
arXiv preprint arXiv:1602.05179 914, 2016
Generalization of Equilibrium Propagation to Vector Field Dynamics
B Scellier, A Goyal, J Binas, T Mesnard, Y Bengio
arXiv preprint arXiv:1808.04873, 2018
Equivalence of equilibrium propagation and recurrent backpropagation
B Scellier, Y Bengio
Neural computation 31 (2), 312-329, 2019
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
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
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
arXiv preprint arXiv:2006.03824, 2020
Equilibrium Propagation with Continual Weight Updates
M Ernoult, J Grollier, D Querlioz, Y Bengio, B Scellier
arXiv preprint arXiv:2005.04168, 2020
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
Continual Weight Updates and Convolutional Architectures for Equilibrium Propagation
M Ernoult, J Grollier, D Querlioz, Y Bengio, B Scellier
arXiv preprint arXiv:2005.04169, 2020
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