Benjamin Scellier

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 23

Top Topics

Games With Incomplete Information

Top Venues

Frontiers Comput. Neurosci.

Publications

Benjamin Scellier
A Fast Algorithm to Simulate Nonlinear Resistive Networks. CoRR (2024)
Vidyesh Rao Anisetti, Ananth Kandala, Benjamin Scellier, J. M. Schwarz
Frequency Propagation: Multimechanism Learning in Nonlinear Physical Networks. Neural Comput. 36 (4) (2024)
Ali Momeni, Babak Rahmani, Benjamin Scellier, Logan G. Wright, Peter L. McMahon, Clara C. Wanjura, Yuhang Li, Anas Skalli, Natalia G. Berloff, Tatsuhiro Onodera, Ilker Oguz, Francesco Morichetti, Philipp del Hougne, Manuel Le Gallo, Abu Sebastian, Azalia Mirhoseini, Cheng Zhang, Danijela Markovic, Daniel Brunner, Christophe Moser, Sylvain Gigan, Florian Marquardt, Aydogan Ozcan, Julie Grollier, Andrea J. Liu, Demetri Psaltis, Andrea Alù, Romain Fleury
Training of Physical Neural Networks. CoRR (2024)
Benjamin Scellier
Quantum Equilibrium Propagation: Gradient-Descent Training of Quantum Systems. CoRR (2024)
Benjamin Scellier, Maxence Ernoult, Jack D. Kendall, Suhas Kumar
Energy-based learning algorithms for analog computing: a comparative study. NeurIPS (2023)
Benjamin Scellier, Maxence Ernoult, Jack D. Kendall, Suhas Kumar
Energy-based learning algorithms for analog computing: a comparative study. CoRR (2023)
Benjamin Scellier, Siddhartha Mishra
A universal approximation theorem for nonlinear resistive networks. CoRR (2023)
Benjamin Scellier, Siddhartha Mishra, Yoshua Bengio, Yann Ollivier
Agnostic Physics-Driven Deep Learning. CoRR (2022)
Axel Laborieux, Maxence Ernoult, Benjamin Scellier, Yoshua Bengio, Julie Grollier, Damien Querlioz
Scaling Equilibrium Propagation to Deep ConvNets by Drastically Reducing its Gradient Estimator Bias. CoRR (2021)
Benjamin Scellier
A deep learning theory for neural networks grounded in physics. CoRR (2021)
Axel Laborieux, Maxence Ernoult, Benjamin Scellier, Yoshua Bengio, Julie Grollier, Damien Querlioz
Scaling Equilibrium Propagation to Deep ConvNets by Drastically Reducing its Gradient Estimator Bias. CoRR (2020)
Maxence Ernoult, Julie Grollier, Damien Querlioz, Yoshua Bengio, Benjamin Scellier
Continual Weight Updates and Convolutional Architectures for Equilibrium Propagation. CoRR (2020)
Jack D. Kendall, Ross D. Pantone, Kalpana Manickavasagam, Yoshua Bengio, Benjamin Scellier
Training End-to-End Analog Neural Networks with Equilibrium Propagation. CoRR (2020)
Maxence Ernoult, Julie Grollier, Damien Querlioz, Yoshua Bengio, Benjamin Scellier
Equilibrium Propagation with Continual Weight Updates. CoRR (2020)
Benjamin Scellier, Yoshua Bengio
Equivalence of Equilibrium Propagation and Recurrent Backpropagation. Neural Comput. 31 (2) (2019)
Maxence Ernoult, Julie Grollier, Damien Querlioz, Yoshua Bengio, Benjamin Scellier
Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input. NeurIPS (2019)
Maxence Ernoult, Julie Grollier, Damien Querlioz, Yoshua Bengio, Benjamin Scellier
Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input. CoRR (2019)
Benjamin Scellier, Anirudh Goyal, Jonathan Binas, Thomas Mesnard, Yoshua Bengio
Generalization of Equilibrium Propagation to Vector Field Dynamics. CoRR (2018)
Benjamin Scellier, Anirudh Goyal, Jonathan Binas, Thomas Mesnard, Yoshua Bengio
Extending the Framework of Equilibrium Propagation to General Dynamics. ICLR (Workshop) (2018)
Benjamin Scellier, Yoshua Bengio
Equilibrium Propagation: Bridging the Gap between Energy-Based Models and Backpropagation. Frontiers Comput. Neurosci. 11 (2017)
Benjamin Scellier, Yoshua Bengio
Equivalence of Equilibrium Propagation and Recurrent Backpropagation. CoRR (2017)
Benjamin Scellier, Yoshua Bengio
Towards a Biologically Plausible Backprop. CoRR (2016)
Yoshua Bengio, Benjamin Scellier, Olexa Bilaniuk, João Sacramento, Walter Senn
Feedforward Initialization for Fast Inference of Deep Generative Networks is biologically plausible. CoRR (2016)