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

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

6 June 2020

Papers citing "Scaling Equilibrium Propagation to Deep ConvNets by Drastically Reducing its Gradient Estimator Bias"

16 / 16 papers shown

Title
Equilibrium Propagation for Learning in Lagrangian Dynamical Systems Serge Massar 26 0 0 12 May 2025
Self-Contrastive Forward-Forward Algorithm Xing Chen Dongshu Liu Jérémie Laydevant Julie Grollier 44 2 0 17 Sep 2024
Scaling SNNs Trained Using Equilibrium Propagation to Convolutional Architectures Jiaqi Lin Malyaban Bal Abhronil Sengupta 42 2 0 04 May 2024
Improving equilibrium propagation without weight symmetry through Jacobian homeostasis Axel Laborieux Friedemann Zenke 25 7 0 05 Sep 2023
Correlative Information Maximization: A Biologically Plausible Approach to Supervised Deep Neural Networks without Weight Symmetry Bariscan Bozkurt Cengiz Pehlevan A. Erdogan 35 1 0 07 Jun 2023
Understanding and Improving Optimization in Predictive Coding Networks Nick Alonso J. Krichmar Emre Neftci 73 7 0 23 May 2023
Dual Propagation: Accelerating Contrastive Hebbian Learning with Dyadic Neurons R. Høier D. Staudt Christopher Zach 31 11 0 02 Feb 2023
Hebbian Deep Learning Without Feedback Adrien Journé Hector Garcia Rodriguez Qinghai Guo Timoleon Moraitis AAML 31 49 0 23 Sep 2022
Sequence Learning Using Equilibrium Propagation Malyaban Bal Abhronil Sengupta 35 9 0 14 Sep 2022
Biologically-inspired neuronal adaptation improves learning in neural networks Yoshimasa Kubo Eric Chalmers Artur Luczak 17 6 0 08 Apr 2022
Error-driven Input Modulation: Solving the Credit Assignment Problem without a Backward Pass Giorgia Dellaferrera Gabriel Kreiman 29 53 0 27 Jan 2022
Towards Biologically Plausible Convolutional Networks Roman Pogodin Yash Mehta Timothy Lillicrap P. Latham 26 22 0 22 Jun 2021
Training Dynamical Binary Neural Networks with Equilibrium Propagation Jérémie Laydevant M. Ernoult D. Querlioz Julie Grollier 26 16 0 16 Mar 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
Local plasticity rules can learn deep representations using self-supervised contrastive predictions Bernd Illing Jean-Paul Ventura G. Bellec W. Gerstner SSL DRL 59 69 0 16 Oct 2020
Kernelized information bottleneck leads to biologically plausible 3-factor Hebbian learning in deep networks Roman Pogodin P. Latham 24 34 0 12 Jun 2020