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 / 97 papers shown

Title
Equilibrium Propagation for Learning in Lagrangian Dynamical Systems Serge Massar 26 0 0 12 May 2025
Harnessing uncertainty when learning through Equilibrium Propagation in neural networks Jonathan Peters Philippe Talatchian 42 0 0 28 Mar 2025
Training Large Neural Networks With Low-Dimensional Error Feedback Maher Hanut Jonathan Kadmon 45 1 0 27 Feb 2025
Analog In-memory Training on General Non-ideal Resistive Elements: The Impact of Response Functions Zhaoxian Wu Quan Xian Tayfun Gokmen Omobayode Fagbohungbe Tianyi Chen 91 0 0 17 Feb 2025
Benchmarking Predictive Coding Networks -- Made Simple Luca Pinchetti Chang Qi Oleh Lokshyn Gaspard Olivers Cornelius Emde ... Simon Frieder Bayar I. Menzat Rafal Bogacz Thomas Lukasiewicz Tommaso Salvatori 130 5 0 17 Feb 2025
Local Loss Optimization in the Infinite Width: Stable Parameterization of Predictive Coding Networks and Target Propagation Satoki Ishikawa Rio Yokota Ryo Karakida 46 0 0 04 Nov 2024
Provable Accuracy Bounds for Hybrid Dynamical Optimization and Sampling Matthew Burns Qingyuan Hou Michael Huang 188 1 0 08 Oct 2024
Tight Stability, Convergence, and Robustness Bounds for Predictive Coding Networks A. Mali Tommaso Salvatori Alexander Ororbia 37 0 0 07 Oct 2024
Relating Superconducting Optoelectronic Networks to Classical Neurodynamics J. Shainline Bryce Primavera Ryan O'Loughlin 29 0 0 26 Sep 2024
Self-Contrastive Forward-Forward Algorithm Xing Chen Dongshu Liu Jérémie Laydevant Julie Grollier 44 2 0 17 Sep 2024
Predictive Coding Networks and Inference Learning: Tutorial and Survey B. V. Zwol Ro Jefferson E. V. D. Broek 58 0 0 04 Jul 2024
Calibrating Neural Networks' parameters through Optimal Contraction in a Prediction Problem Valdes Gonzalo 34 0 0 15 Jun 2024
Contribute to balance, wire in accordance: Emergence of backpropagation from a simple, bio-plausible neuroplasticity rule Xinhao Fan S. P. Mysore 37 0 0 23 May 2024
Scaling SNNs Trained Using Equilibrium Propagation to Convolutional Architectures Jiaqi Lin Malyaban Bal Abhronil Sengupta 42 2 0 04 May 2024
Backpropagation through space, time, and the brain B. Ellenberger Paul Haider Jakob Jordan Kevin Max Ismael Jaras Laura Kriener Federico Benitez Mihai A. Petrovici 133 8 0 25 Mar 2024
Evolutionary algorithms as an alternative to backpropagation for supervised training of Biophysical Neural Networks and Neural ODEs James Hazelden Yuhan Helena Liu Eli Shlizerman E. Shea-Brown 47 2 0 17 Nov 2023
Randomized Forward Mode of Automatic Differentiation For Optimization Algorithms Khemraj Shukla Yeonjong Shin ODL 26 4 0 22 Oct 2023
Seeking Next Layer Neurons' Attention for Error-Backpropagation-Like Training in a Multi-Agent Network Framework Arshia Soltani Moakhar Mohammad Azizmalayeri Hossein Mirzaei M. T. Manzuri M. Rohban 31 2 0 15 Oct 2023
Neural Sampling in Hierarchical Exponential-family Energy-based Models Xingsi Dong Si Wu 38 2 0 12 Oct 2023
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
Biologically-Motivated Learning Model for Instructed Visual Processing R. Abel S. Ullman 25 0 0 04 Jun 2023
Block-local learning with probabilistic latent representations David Kappel Khaleelulla Khan Nazeer Cabrel Teguemne Fokam Christian Mayr Anand Subramoney 24 4 0 24 May 2023
Understanding and Improving Optimization in Predictive Coding Networks Nick Alonso J. Krichmar Emre Neftci 73 7 0 23 May 2023
Backpropagation-free Training of Deep Physical Neural Networks Ali Momeni Babak Rahmani M. Malléjac Philipp del Hougne Romain Fleury AI4CE PINN 32 54 0 20 Apr 2023
Flexible Phase Dynamics for Bio-Plausible Contrastive Learning Ezekiel Williams C. Bredenberg Guillaume Lajoie 32 6 0 24 Feb 2023
Dataset Distillation with Convexified Implicit Gradients Noel Loo Ramin Hasani Mathias Lechner Daniela Rus DD 31 41 0 13 Feb 2023
Dual Propagation: Accelerating Contrastive Hebbian Learning with Dyadic Neurons R. Høier D. Staudt Christopher Zach 31 11 0 02 Feb 2023
The Forward-Forward Algorithm: Some Preliminary Investigations Geoffrey E. Hinton 27 260 0 27 Dec 2022
Is Bio-Inspired Learning Better than Backprop? Benchmarking Bio Learning vs. Backprop Manas Gupta Sarthak Ketanbhai Modi Hang Zhang Joon Hei Lee J. Lim 27 7 0 09 Dec 2022
Convolutional Neural Generative Coding: Scaling Predictive Coding to Natural Images Alexander Ororbia A. Mali BDL 38 10 0 22 Nov 2022
A Stable, Fast, and Fully Automatic Learning Algorithm for Predictive Coding Networks Tommaso Salvatori Yuhang Song Yordan Yordanov Beren Millidge Zheng R. Xu Lei Sha Cornelius Emde Rafal Bogacz Thomas Lukasiewicz 34 10 0 16 Nov 2022
Predictive Coding beyond Gaussian Distributions Luca Pinchetti Tommaso Salvatori Yordan Yordanov Beren Millidge Yuhang Song Thomas Lukasiewicz UQCV BDL 32 11 0 07 Nov 2022
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 Plausible Training of Deep Neural Networks Using a Top-down Credit Assignment Network Jian-Hui Chen Cheng-Lin Liu Zuoren Wang 26 0 0 01 Aug 2022
The Free Energy Principle drives neuromorphic development C. Fields Karl J. Friston J. Glazebrook Michael Levin A. Marcianò 35 14 0 20 Jul 2022
Biologically-inspired neuronal adaptation improves learning in neural networks Yoshimasa Kubo Eric Chalmers Artur Luczak 17 6 0 08 Apr 2022
Hybrid Predictive Coding: Inferring, Fast and Slow Alexander Tschantz Beren Millidge A. Seth Christopher L. Buckley 27 36 0 05 Apr 2022
Quantum materials for energy-efficient neuromorphic computing A. Hoffmann S. Ramanathan Julie Grollier A. Kent M. Rozenberg ... A. Petford-Long J. Schuller M. D. Stiles Y. Takamura Yimei Zhu 11 46 0 04 Apr 2022
Signal Propagation: A Framework for Learning and Inference In a Forward Pass Adam A. Kohan E. Rietman H. Siegelmann 24 26 0 04 Apr 2022
Predicting Multi-Antenna Frequency-Selective Channels via Meta-Learned Linear Filters based on Long-Short Term Channel Decomposition Sangwoo Park Osvaldo Simeone 34 4 0 23 Mar 2022
Constrained Parameter Inference as a Principle for Learning Nasir Ahmad Ellen Schrader Marcel van Gerven 18 10 0 22 Mar 2022
An STDP-Based Supervised Learning Algorithm for Spiking Neural Networks Zhan Hu Tao Wang Xiaolin Hu 15 12 0 07 Mar 2022
Towards Scaling Difference Target Propagation by Learning Backprop Targets M. Ernoult Fabrice Normandin A. Moudgil Sean Spinney Eugene Belilovsky Irina Rish Blake A. Richards Yoshua Bengio 19 28 0 31 Jan 2022
Neural Network Training with Asymmetric Crosspoint Elements M. Onen Tayfun Gokmen T. Todorov T. Nowicki Jesús A. del Alamo J. Rozen W. Haensch Seyoung Kim 34 19 0 31 Jan 2022
Learning on Arbitrary Graph Topologies via Predictive Coding Tommaso Salvatori Luca Pinchetti Beren Millidge Yuhang Song Tianyi Bao Rafal Bogacz Thomas Lukasiewicz 38 33 0 31 Jan 2022
Error-driven Input Modulation: Solving the Credit Assignment Problem without a Backward Pass Giorgia Dellaferrera Gabriel Kreiman 29 53 0 27 Jan 2022
Accurate online training of dynamical spiking neural networks through Forward Propagation Through Time Bojian Yin Federico Corradi S. Bohté 38 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