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

Frontiers in Computational Neuroscience
Benjamin Scellier, Yoshua Bengio

Abstract

We introduce Equilibrium Propagation, a learning framework for energy-based models. It involves only one kind of neural computation, performed in both the first phase (when the prediction is made) and the second phase of training (after the target or prediction error is revealed). Although this algorithm computes the gradient of an objective function just like Backpropagation, it does not need a special computation or circuit for the second phase, where errors are implicitly propagated. Equilibrium Propagation shares similarities with Contrastive Hebbian Learning and Contrastive Divergence while solving the theoretical issues of both algorithms: our algorithm computes the gradient of a well-defined objective function. Because the objective function is defined in terms of local perturbations, the second phase of Equilibrium Propagation corresponds to only nudging the prediction (fixed point or stationary distribution) toward a configuration that reduces prediction error. In the case of a recurrent multi-layer supervised network, the output units are slightly nudged toward their target in the second phase, and the perturbation introduced at the output layer propagates backward in the hidden layers. We show that the signal "back-p...Continue Reading

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Citations

Apr 14, 2018·Neural Computation·Hesham Mostafa, Gert Cauwenberghs
Aug 2, 2018·PLoS Computational Biology·Nathan InselBlake A Richards
Oct 17, 2018·PloS One·Silvan Quax, Marcel van Gerven
Nov 14, 2018·Nanotechnology·Chul-Heung KimJong-Ho Lee
Nov 18, 2018·Interface Focus·Luca SagliettiRiccardo Zecchina
Dec 24, 2018·Neural Computation·Benjamin Scellier, Yoshua Bengio
Feb 17, 2018·Nature Reviews. Neuroscience·Pieter R Roelfsema, Anthony Holtmaat
Jan 30, 2018·Frontiers in Computational Neuroscience·Marcel van Gerven
Aug 17, 2020·Neural Computation·Wei Sun, Jeff Orchard
Sep 21, 2018·Frontiers in Neuroscience·Hesham MostafaGert Cauwenberghs
Mar 31, 2019·Proceedings of the National Academy of Sciences of the United States of America·Dmitry Krotov, John J Hopfield
Apr 9, 2020·Frontiers in Neuroscience·Gianluca ZoppoFernando Corinto
Apr 19, 2020·Nature Reviews. Neuroscience·Timothy P LillicrapGeoffrey Hinton
Jun 18, 2020·Proceedings of the National Academy of Sciences of the United States of America·Menachem SternArvind Murugan
Aug 10, 2018·Network Neuroscience·Christopher J HoneyAnna C Schapiro
Aug 9, 2019·Annual Review of Vision Science·Thomas Serre
Mar 3, 2020·Frontiers in Computational Neuroscience·Mengting ShiYi Zeng
Mar 13, 2020·Frontiers in Computational Neuroscience·Jan KaiserSupriyo Datta
Nov 27, 2018·Frontiers in Human Neuroscience·Praveen K PillyRajan Bhattacharyya
Oct 30, 2019·Nature Neuroscience·Blake A RichardsKonrad P Kording
Dec 8, 2020·Frontiers in Computational Neuroscience·Dongcheng ZhaoFeifei Zhao
Feb 23, 2021·Neural Computation·Shanshan QinCengiz Pehlevan
Mar 9, 2021·Frontiers in Neuroscience·Shuangming YangBernabe Linares-Barranco
Mar 9, 2021·Frontiers in Neuroscience·Axel LaborieuxDamien Querlioz
Jul 31, 2019·Trends in Cognitive Sciences·Victoria J H RitvoKenneth A Norman
May 7, 2021·Nature Communications·Axel LaborieuxDamien Querlioz
Aug 17, 2021·Frontiers in Neuroscience·Ahana Gangopadhyay, Shantanu Chakrabartty
Feb 7, 2020··Pavel KrsekIgor Farkaš

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