Benjamin Scellier

According to our database, Benjamin Scellier authored at least 21 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Frequency Propagation: Multimechanism Learning in Nonlinear Physical Networks.

Vidyesh Rao Anisetti, Ananth Kandala, Benjamin Scellier, J. M. Schwarz

Neural Comput., April, 2024

Training of Physical Neural Networks.

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

CoRR, 2024

Quantum Equilibrium Propagation: Gradient-Descent Training of Quantum Systems.

Benjamin Scellier

CoRR, 2024

A fast algorithm to simulate nonlinear resistive networks.

Benjamin Scellier

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

A universal approximation theorem for nonlinear resistive networks.

Benjamin Scellier, Siddhartha Mishra

CoRR, 2023

Energy-based learning algorithms for analog computing: a comparative study.

Benjamin Scellier, Maxence Ernoult, Jack D. Kendall, Suhas Kumar

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Frequency propagation: Multi-mechanism learning in nonlinear physical networks.

Vidyesh Rao Anisetti, Ananth Kandala, Benjamin Scellier, J. M. Schwarz

CoRR, 2022

Agnostic Physics-Driven Deep Learning.

Benjamin Scellier, Siddhartha Mishra, Yoshua Bengio, Yann Ollivier

CoRR, 2022

Learning by non-interfering feedback chemical signaling in physical networks.

Vidyesh Rao Anisetti, Benjamin Scellier, J. M. Schwarz

CoRR, 2022

2021

A deep learning theory for neural networks grounded in physics.

Benjamin Scellier

CoRR, 2021

2020

Scaling Equilibrium Propagation to Deep ConvNets by Drastically Reducing its Gradient Estimator Bias.

Axel Laborieux, Maxence Ernoult, Benjamin Scellier, Yoshua Bengio, Julie Grollier, Damien Querlioz

CoRR, 2020

Training End-to-End Analog Neural Networks with Equilibrium Propagation.

Jack D. Kendall, Ross D. Pantone, Kalpana Manickavasagam, Yoshua Bengio, Benjamin Scellier

CoRR, 2020

Continual Weight Updates and Convolutional Architectures for Equilibrium Propagation.

Maxence Ernoult, Julie Grollier, Damien Querlioz, Yoshua Bengio, Benjamin Scellier

CoRR, 2020

Equilibrium Propagation with Continual Weight Updates.

Maxence Ernoult, Julie Grollier, Damien Querlioz, Yoshua Bengio, Benjamin Scellier

CoRR, 2020

2019

Equivalence of Equilibrium Propagation and Recurrent Backpropagation.

Benjamin Scellier, Yoshua Bengio

Neural Comput., 2019

Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input.

Maxence Ernoult, Julie Grollier, Damien Querlioz, Yoshua Bengio, Benjamin Scellier

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Generalization of Equilibrium Propagation to Vector Field Dynamics.

Benjamin Scellier, Anirudh Goyal, Jonathan Binas, Thomas Mesnard, Yoshua Bengio

CoRR, 2018

Extending the Framework of Equilibrium Propagation to General Dynamics.

Benjamin Scellier, Anirudh Goyal, Jonathan Binas, Thomas Mesnard, Yoshua Bengio

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Equilibrium Propagation: Bridging the Gap between Energy-Based Models and Backpropagation.

Benjamin Scellier, Yoshua Bengio

Frontiers Comput. Neurosci., 2017

2016

Towards a Biologically Plausible Backprop.

Benjamin Scellier, Yoshua Bengio

CoRR, 2016

Feedforward Initialization for Fast Inference of Deep Generative Networks is biologically plausible.

Yoshua Bengio, Benjamin Scellier, Olexa Bilaniuk, João Sacramento, Walter Senn

CoRR, 2016