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

16 February 2016

Papers citing "Equilibrium Propagation: Bridging the Gap Between Energy-Based Models and Backpropagation"

50 / 107 papers shown

Title
Learning on Arbitrary Graph Topologies via Predictive Coding Tommaso Salvatori Luca Pinchetti Beren Millidge Yuhang Song Tianyi Bao Rafal Bogacz Thomas Lukasiewicz 40 33 0 31 Jan 2022
Error-driven Input Modulation: Solving the Credit Assignment Problem without a Backward Pass Giorgia Dellaferrera Gabriel Kreiman 34 53 0 27 Jan 2022
Accurate online training of dynamical spiking neural networks through Forward Propagation Through Time Bojian Yin Federico Corradi S. Bohté 43 61 0 20 Dec 2021
AdaSTE: An Adaptive Straight-Through Estimator to Train Binary Neural Networks Huu Le R. Høier Che-Tsung Lin Christopher Zach 55 17 0 06 Dec 2021
Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons Paul Haider B. Ellenberger Laura Kriener Jakob Jordan Walter Senn Mihai A. Petrovici 27 24 0 27 Oct 2021
An energy-based model for neuro-symbolic reasoning on knowledge graphs Dominik Dold J. Garrido AI4CE 30 8 0 04 Oct 2021
Predicting Flat-Fading Channels via Meta-Learned Closed-Form Linear Filters and Equilibrium Propagation Sangwoo Park Osvaldo Simeone 47 8 0 01 Oct 2021
Capturing the objects of vision with neural networks B. Peters N. Kriegeskorte OCL 33 56 0 07 Sep 2021
SoftHebb: Bayesian Inference in Unsupervised Hebbian Soft Winner-Take-All Networks Timoleon Moraitis Dmitry Toichkin Adrien Journé Yansong Chua Qinghai Guo AAML BDL 68 28 0 12 Jul 2021
Backprop-Free Reinforcement Learning with Active Neural Generative Coding Alexander Ororbia A. Mali 41 15 0 10 Jul 2021
Applications of the Free Energy Principle to Machine Learning and Neuroscience Beren Millidge DRL 28 7 0 30 Jun 2021
On the relationship between predictive coding and backpropagation Robert Rosenbaum 38 28 0 20 Jun 2021
Training Dynamical Binary Neural Networks with Equilibrium Propagation Jérémie Laydevant M. Ernoult D. Querlioz Julie Grollier 26 16 0 16 Mar 2021
Reverse Differentiation via Predictive Coding Tommaso Salvatori Yuhang Song Thomas Lukasiewicz Rafal Bogacz Zhenghua Xu PINN 30 26 0 08 Mar 2021
Predictive Coding Can Do Exact Backpropagation on Convolutional and Recurrent Neural Networks Tommaso Salvatori Yuhang Song Thomas Lukasiewicz Rafal Bogacz Zhenghua Xu PINN 29 24 0 05 Mar 2021
The Yin-Yang dataset Laura Kriener Julian Goltz Mihai A. Petrovici 3DH 35 19 0 16 Feb 2021
Training Deep Architectures Without End-to-End Backpropagation: A Survey on the Provably Optimal Methods Shiyu Duan José C. Príncipe MQ 38 3 0 09 Jan 2021
Improved Contrastive Divergence Training of Energy Based Models Yilun Du Shuang Li J. Tenenbaum Igor Mordatch 43 139 0 02 Dec 2020
Energy-Based Models for Continual Learning Shuang Li Yilun Du Gido M. van de Ven Igor Mordatch 32 42 0 24 Nov 2020
Local plasticity rules can learn deep representations using self-supervised contrastive predictions Bernd Illing Jean-Paul Ventura G. Bellec W. Gerstner SSL DRL 59 70 0 16 Oct 2020
Why Layer-Wise Learning is Hard to Scale-up and a Possible Solution via Accelerated Downsampling Wenchi Ma Miao Yu Kaidong Li Guanghui Wang 17 5 0 15 Oct 2020
EqSpike: Spike-driven Equilibrium Propagation for Neuromorphic Implementations Erwann Martin M. Ernoult Jérémie Laydevant Shuai-shuai Li D. Querlioz Teodora Petrisor Julie Grollier 27 49 0 15 Oct 2020
Tuning Convolutional Spiking Neural Network with Biologically-plausible Reward Propagation Tielin Zhang Shuncheng Jia Xiang Cheng Bo Xu 36 48 0 09 Oct 2020
Deriving Differential Target Propagation from Iterating Approximate Inverses Yoshua Bengio 20 25 0 29 Jul 2020
Kernelized information bottleneck leads to biologically plausible 3-factor Hebbian learning in deep networks Roman Pogodin P. Latham 27 34 0 12 Jun 2020
GAIT-prop: A biologically plausible learning rule derived from backpropagation of error Nasir Ahmad Marcel van Gerven L. Ambrogioni AAML 20 25 0 11 Jun 2020
Predictive Coding Approximates Backprop along Arbitrary Computation Graphs Beren Millidge Alexander Tschantz Christopher L. Buckley 32 118 0 07 Jun 2020
An Overview of Neural Network Compression James OÑeill AI4CE 47 98 0 05 Jun 2020
Equilibrium Propagation with Continual Weight Updates M. Ernoult Julie Grollier D. Querlioz Yoshua Bengio B. Scellier 14 38 0 29 Apr 2020
Truncated Inference for Latent Variable Optimization Problems: Application to Robust Estimation and Learning Christopher Zach Huu Le 36 4 0 12 Mar 2020
Synaptic Metaplasticity in Binarized Neural Networks Axel Laborieux M. Ernoult T. Hirtzlin D. Querlioz CLL 28 62 0 07 Mar 2020
Two Routes to Scalable Credit Assignment without Weight Symmetry D. Kunin Aran Nayebi Javier Sagastuy-Breña Surya Ganguli Jonathan M. Bloom Daniel L. K. Yamins 36 32 0 28 Feb 2020
Contrastive Similarity Matching for Supervised Learning Shanshan Qin N. Mudur Cengiz Pehlevan SSL DRL 22 1 0 24 Feb 2020
Large-Scale Gradient-Free Deep Learning with Recursive Local Representation Alignment Alexander Ororbia A. Mali Daniel Kifer C. Lee Giles 23 2 0 10 Feb 2020
Ghost Units Yield Biologically Plausible Backprop in Deep Neural Networks Thomas Mesnard Gaetan Vignoud João Sacramento Walter Senn Yoshua Bengio 27 7 0 15 Nov 2019
Making Predictive Coding Networks Generative Jeff Orchard Wei Sun 14 1 0 26 Oct 2019
Spike-based causal inference for weight alignment Jordan Guerguiev Konrad Paul Kording Blake A. Richards CML 25 23 0 03 Oct 2019
Spiking Neural Predictive Coding for Continual Learning from Data Streams Alexander Ororbia 25 25 0 23 Aug 2019
Resonant Machine Learning Based on Complex Growth Transform Dynamical Systems Oindrila Chatterjee S. Chakrabartty 27 7 0 15 Aug 2019
Putting An End to End-to-End: Gradient-Isolated Learning of Representations Sindy Löwe Peter O'Connor Bastiaan S. Veeling SSL 14 143 0 28 May 2019
Contrastive Learning for Lifted Networks Christopher Zach V. Estellers SSL 17 12 0 07 May 2019
Biologically plausible deep learning -- but how far can we go with shallow networks? Bernd Illing W. Gerstner Johanni Brea 30 94 0 27 Feb 2019
Optimal Kronecker-Sum Approximation of Real Time Recurrent Learning Frederik Benzing M. Gauy Asier Mujika A. Martinsson Angelika Steger 23 23 0 11 Feb 2019
Training Neural Networks with Local Error Signals Arild Nøkland L. Eidnes 32 226 0 20 Jan 2019
A Biologically Plausible Learning Rule for Deep Learning in the Brain Isabella Pozzi Michael Felsberg Fahad Shahbaz Khan AI4CE 12 31 0 05 Nov 2018
Dendritic cortical microcircuits approximate the backpropagation algorithm João Sacramento Rui Ponte Costa Yoshua Bengio Walter Senn 36 308 0 26 Oct 2018
Continual Learning of Recurrent Neural Networks by Locally Aligning Distributed Representations Alexander Ororbia A. Mali C. Lee Giles Daniel Kifer 29 63 0 17 Oct 2018
Error Forward-Propagation: Reusing Feedforward Connections to Propagate Errors in Deep Learning Adam A. Kohan E. Rietman H. Siegelmann 58 24 0 09 Aug 2018
Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures Sergey Bartunov Adam Santoro Blake A. Richards Luke Marris Geoffrey E. Hinton Timothy Lillicrap 40 240 0 12 Jul 2018
Unsupervised Learning by Competing Hidden Units Dmitry Krotov J. Hopfield SSL 20 166 0 26 Jun 2018