Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures

23 June 2020

Papers citing "Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures"

43 / 43 papers shown

Title
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 127 5 0 17 Feb 2025
Counter-Current Learning: A Biologically Plausible Dual Network Approach for Deep Learning Chia-Hsiang Kao Bharath Hariharan 34 1 0 30 Sep 2024
Is All Learning (Natural) Gradient Descent? Lucas Shoji Kenta Suzuki Leo Kozachkov 28 1 0 24 Sep 2024
Self-Contrastive Forward-Forward Algorithm Xing Chen Dongshu Liu Jérémie Laydevant Julie Grollier 34 2 0 17 Sep 2024
Training Spiking Neural Networks via Augmented Direct Feedback Alignment Yongbo Zhang Katsuma Inoue M. Nakajima Toshikazu Hashimoto Yasuo Kuniyoshi Kohei Nakajima 30 0 0 12 Sep 2024
Online Pseudo-Zeroth-Order Training of Neuromorphic Spiking Neural Networks Mingqing Xiao Qingyan Meng Zongpeng Zhang D.K. He Zhouchen Lin 32 0 0 17 Jul 2024
Training of Physical Neural Networks Ali Momeni Babak Rahmani B. Scellier Logan G. Wright Peter L. McMahon ... Julie Grollier Andrea J. Liu D. Psaltis Andrea Alù Romain Fleury PINN AI4CE 51 9 0 05 Jun 2024
A Review of Neuroscience-Inspired Machine Learning Alexander Ororbia A. Mali Adam Kohan Beren Millidge Tommaso Salvatori 27 7 0 16 Feb 2024
Forward Direct Feedback Alignment for Online Gradient Estimates of Spiking Neural Networks Florian Bacho Dminique Chu 12 0 0 06 Feb 2024
Convergence guarantees for forward gradient descent in the linear regression model Thijs Bos Johannes Schmidt-Hieber 22 3 0 26 Sep 2023
Improving equilibrium propagation without weight symmetry through Jacobian homeostasis Axel Laborieux Friedemann Zenke 12 7 0 05 Sep 2023
Random Feedback Alignment Algorithms to train Neural Networks: Why do they Align? Dominique F. Chu Florian Bacho ODL 17 0 0 04 Jun 2023
A General Framework for Interpretable Neural Learning based on Local Information-Theoretic Goal Functions Abdullah Makkeh Marcel Graetz Andreas C. Schneider David A. Ehrlich V. Priesemann Michael Wibral 44 1 0 03 Jun 2023
Implicit Regularization in Feedback Alignment Learning Mechanisms for Neural Networks Zachary Robertson Oluwasanmi Koyejo 23 0 0 02 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
Learning with augmented target information: An alternative theory of Feedback Alignment Huzi Cheng Joshua W. Brown CVBM 11 0 0 03 Apr 2023
Forward Learning with Top-Down Feedback: Empirical and Analytical Characterization R. Srinivasan Francesca Mignacco M. Sorbaro Maria Refinetti A. Cooper Gabriel Kreiman Giorgia Dellaferrera 19 15 0 10 Feb 2023
Biologically Plausible Learning on Neuromorphic Hardware Architectures Christopher Wolters Brady Taylor Edward Hanson Xiaoxuan Yang Ulf Schlichtmann Yiran Chen 11 3 0 29 Dec 2022
Low-Variance Forward Gradients using Direct Feedback Alignment and Momentum Florian Bacho Dominique F. Chu 13 7 0 14 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 22 7 0 09 Dec 2022
Scaling Laws Beyond Backpropagation Matthew J. Filipovich Alessandro Cappelli Daniel Hesslow Julien Launay 19 3 0 26 Oct 2022
The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks Blake Bordelon C. Pehlevan 41 22 0 05 Oct 2022
Holomorphic Equilibrium Propagation Computes Exact Gradients Through Finite Size Oscillations Axel Laborieux Friedemann Zenke 33 33 0 01 Sep 2022
Backpropagation at the Infinitesimal Inference Limit of Energy-Based Models: Unifying Predictive Coding, Equilibrium Propagation, and Contrastive Hebbian Learning Beren Millidge Yuhang Song Tommaso Salvatori Thomas Lukasiewicz Rafal Bogacz 13 21 0 31 May 2022
A comparative study of back propagation and its alternatives on multilayer perceptrons John F. Waldo AAML 14 1 0 31 May 2022
Emergent organization of receptive fields in networks of excitatory and inhibitory neurons Leon Lufkin Ashish Puri Ganlin Song Xinyi Zhong John D. Lafferty 6 1 0 26 May 2022
Physical Deep Learning with Biologically Plausible Training Method M. Nakajima Katsuma Inoue Kenji Tanaka Yasuo Kuniyoshi Toshikazu Hashimoto Kohei Nakajima AI4CE 28 3 0 01 Apr 2022
How and When Random Feedback Works: A Case Study of Low-Rank Matrix Factorization Shivam Garg Santosh Vempala 20 3 0 17 Nov 2021
Silicon Photonic Architecture for Training Deep Neural Networks with Direct Feedback Alignment M. Filipovich Zhimu Guo M. Al-Qadasi Bicky A. Marquez Hugh Morison V. Sorger Paul R. Prucnal S. Shekhar B. Shastri 20 52 0 12 Nov 2021
Convergence Analysis and Implicit Regularization of Feedback Alignment for Deep Linear Networks M. Girotti Ioannis Mitliagkas Gauthier Gidel 14 1 0 20 Oct 2021
ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients Alessandro Cappelli Julien Launay Laurent Meunier Ruben Ohana Iacopo Poli AAML 16 4 0 06 Jul 2021
How to Train Your Wide Neural Network Without Backprop: An Input-Weight Alignment Perspective Akhilan Boopathy Ila Fiete 16 9 0 15 Jun 2021
Convergence and Alignment of Gradient Descent with Random Backpropagation Weights Ganlin Song Ruitu Xu John D. Lafferty ODL 46 21 0 10 Jun 2021
Credit Assignment Through Broadcasting a Global Error Vector David G. Clark L. F. Abbott SueYeon Chung 17 23 0 08 Jun 2021
Photonic Differential Privacy with Direct Feedback Alignment Ruben Ohana H. M. Ruiz Julien Launay Alessandro Cappelli Iacopo Poli L. Ralaivola A. Rakotomamonjy 14 8 0 07 Jun 2021
Deep physical neural networks enabled by a backpropagation algorithm for arbitrary physical systems Logan G. Wright Tatsuhiro Onodera Martin M. Stein Tianyu Wang Darren T. Schachter Zoey Hu Peter L. McMahon PINN AI4CE 40 469 0 27 Apr 2021
Gradient-adjusted Incremental Target Propagation Provides Effective Credit Assignment in Deep Neural Networks Sander Dalm Nasir Ahmad L. Ambrogioni Marcel van Gerven 10 1 0 23 Feb 2021
Adversarial Robustness by Design through Analog Computing and Synthetic Gradients Alessandro Cappelli Ruben Ohana Julien Launay Laurent Meunier Iacopo Poli Florent Krzakala AAML 54 13 0 06 Jan 2021
Hardware Beyond Backpropagation: a Photonic Co-Processor for Direct Feedback Alignment Julien Launay Iacopo Poli Kilian Muller Gustave Pariente I. Carron L. Daudet Florent Krzakala S. Gigan MoE 15 18 0 11 Dec 2020
Align, then memorise: the dynamics of learning with feedback alignment Maria Refinetti Stéphane dÁscoli Ruben Ohana Sebastian Goldt 26 36 0 24 Nov 2020
Feed-Forward On-Edge Fine-tuning Using Static Synthetic Gradient Modules R. Neven Marian Verhelst Tinne Tuytelaars Toon Goedemé 8 1 0 21 Sep 2020
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism M. Shoeybi M. Patwary Raul Puri P. LeGresley Jared Casper Bryan Catanzaro MoE 245 1,821 0 17 Sep 2019
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 253 3,239 0 24 Nov 2016