Benjamin Scellier

27 papers A* 3Journal 23Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Training of physical neural networks. Nat. 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
2024	J	`jnl`	A Fast Algorithm to Simulate Nonlinear Resistive Networks. CoRR Benjamin Scellier
2024	A*	`conf`	A fast algorithm to simulate nonlinear resistive networks. ICML Benjamin Scellier
2024	J	`jnl`	Frequency Propagation: Multimechanism Learning in Nonlinear Physical Networks. Neural Comput. Vidyesh Rao Anisetti, Ananth Kandala, Benjamin Scellier, J. M. Schwarz
2024	J	`jnl`	Quantum Equilibrium Propagation: Gradient-Descent Training of Quantum Systems. CoRR Benjamin Scellier
2024	J	`jnl`	Training of Physical Neural Networks. CoRR 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
2023	J	`jnl`	A universal approximation theorem for nonlinear resistive networks. CoRR Benjamin Scellier, Siddhartha Mishra
2023	A*	`conf`	Energy-based learning algorithms for analog computing: a comparative study. NeurIPS Benjamin Scellier, Maxence Ernoult, Jack D. Kendall, Suhas Kumar
2023	J	`jnl`	Energy-based learning algorithms for analog computing: a comparative study. CoRR Benjamin Scellier, Maxence Ernoult, Jack D. Kendall, Suhas Kumar
2022	J	`jnl`	Agnostic Physics-Driven Deep Learning. CoRR Benjamin Scellier, Siddhartha Mishra, Yoshua Bengio, Yann Ollivier
2022	J	`jnl`	Frequency propagation: Multi-mechanism learning in nonlinear physical networks. CoRR Vidyesh Rao Anisetti, Ananth Kandala, Benjamin Scellier, J. M. Schwarz
2022	J	`jnl`	Learning by non-interfering feedback chemical signaling in physical networks. CoRR Vidyesh Rao Anisetti, Benjamin Scellier, J. M. Schwarz
2021	J	`jnl`	A deep learning theory for neural networks grounded in physics. CoRR Benjamin Scellier
2021	J	`jnl`	Scaling Equilibrium Propagation to Deep ConvNets by Drastically Reducing its Gradient Estimator Bias. CoRR Axel Laborieux, Maxence Ernoult, Benjamin Scellier, Yoshua Bengio, Julie Grollier, Damien Querlioz
2020	J	`jnl`	Continual Weight Updates and Convolutional Architectures for Equilibrium Propagation. CoRR Maxence Ernoult, Julie Grollier, Damien Querlioz, Yoshua Bengio, Benjamin Scellier
2020	J	`jnl`	Equilibrium Propagation with Continual Weight Updates. CoRR Maxence Ernoult, Julie Grollier, Damien Querlioz, Yoshua Bengio, Benjamin Scellier
2020	J	`jnl`	Scaling Equilibrium Propagation to Deep ConvNets by Drastically Reducing its Gradient Estimator Bias. CoRR Axel Laborieux, Maxence Ernoult, Benjamin Scellier, Yoshua Bengio, Julie Grollier, Damien Querlioz
2020	J	`jnl`	Training End-to-End Analog Neural Networks with Equilibrium Propagation. CoRR Jack D. Kendall, Ross D. Pantone, Kalpana Manickavasagam, Yoshua Bengio, Benjamin Scellier
2019	J	`jnl`	Equivalence of Equilibrium Propagation and Recurrent Backpropagation. Neural Comput. Benjamin Scellier, Yoshua Bengio
2019	A*	`conf`	Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input. NeurIPS Maxence Ernoult, Julie Grollier, Damien Querlioz, Yoshua Bengio, Benjamin Scellier
2019	J	`jnl`	Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input. CoRR Maxence Ernoult, Julie Grollier, Damien Querlioz, Yoshua Bengio, Benjamin Scellier
2018	—	`conf`	Extending the Framework of Equilibrium Propagation to General Dynamics. ICLR (Workshop) Benjamin Scellier, Anirudh Goyal, Jonathan Binas, Thomas Mesnard, Yoshua Bengio
2018	J	`jnl`	Generalization of Equilibrium Propagation to Vector Field Dynamics. CoRR Benjamin Scellier, Anirudh Goyal, Jonathan Binas, Thomas Mesnard, Yoshua Bengio
2017	J	`jnl`	Equilibrium Propagation: Bridging the Gap between Energy-Based Models and Backpropagation. Frontiers Comput. Neurosci. Benjamin Scellier, Yoshua Bengio
2017	J	`jnl`	Equivalence of Equilibrium Propagation and Recurrent Backpropagation. CoRR Benjamin Scellier, Yoshua Bengio
2016	J	`jnl`	Feedforward Initialization for Fast Inference of Deep Generative Networks is biologically plausible. CoRR Yoshua Bengio, Benjamin Scellier, Olexa Bilaniuk, João Sacramento, Walter Senn
2016	J	`jnl`	Towards a Biologically Plausible Backprop. CoRR Benjamin Scellier, Yoshua Bengio