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Benjamin Scellier
Benjamin Scellier
Rain AI
Verifisert e-postadresse på rain.ai - Startside
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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
10002019
Equilibrium propagation: bridging the gap between energy-based models and backpropagation
B Scellier, Y Bengio
Frontiers in computational neuroscience 11, 24, 2017
6182017
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
1042020
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
852021
Equivalence of equilibrium propagation and recurrent backpropagation
B Scellier, Y Bengio
Neural computation 31 (2), 312-329, 2019
542019
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
532019
Generalization of Equilibrium Propagation to Vector Field Dynamics
B Scellier, A Goyal, J Binas, T Mesnard, Y Bengio
arXiv preprint arXiv:1808.04873, 2018
51*2018
Equilibrium Propagation with Continual Weight Updates
M Ernoult, J Grollier, D Querlioz, Y Bengio, B Scellier
arXiv preprint arXiv:2005.04168, 2020
472020
A deep learning theory for neural networks grounded in physics
B Scellier
arXiv preprint arXiv:2103.09985, 2021
332021
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
25*2024
Learning by non-interfering feedback chemical signaling in physical networks
VR Anisetti, B Scellier, JM Schwarz
Physical Review Research 5 (2), 023024, 2023
232023
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
232016
Frequency propagation: Multimechanism learning in nonlinear physical networks
VR Anisetti, A Kandala, B Scellier, JM Schwarz
Neural Computation 36 (4), 596-620, 2024
162024
Training of Physical Neural Networks
A Momeni, B Rahmani, B Scellier, LG Wright, PL McMahon, CC Wanjura, ...
arXiv preprint arXiv:2406.03372, 2024
152024
Agnostic Physics-Driven Deep Learning
B Scellier, S Mishra, Y Bengio, Y Ollivier
arXiv preprint arXiv:2205.15021, 2022
152022
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
82022
A Fast Algorithm to Simulate Nonlinear Resistive Networks
B Scellier
arXiv preprint arXiv:2402.11674, 2024
62024
Contrastive learning through non-equilibrium memory
M Falk, A Strupp, B Scellier, A Murugan
arXiv preprint arXiv:2312.17723, 2023
42023
Quantum Equilibrium Propagation: Gradient-Descent Training of Quantum Systems
B Scellier
arXiv preprint arXiv:2406.00879, 2024
32024
A universal approximation theorem for nonlinear resistive networks
B Scellier, S Mishra
arXiv preprint arXiv:2312.15063, 2023
22023
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Artikler 1–20