Principled Training of Neural Networks with Direct Feedback Alignment

11 June 2019

Papers citing "Principled Training of Neural Networks with Direct Feedback Alignment"

22 / 22 papers shown

Title
Can Local Representation Alignment RNNs Solve Temporal Tasks? Nikolay Manchev Luis C. Garcia-Peraza-Herrera AI4TS 30 0 0 18 Apr 2025
Training Large Neural Networks With Low-Dimensional Error Feedback Maher Hanut Jonathan Kadmon 40 0 0 27 Feb 2025
Training Spiking Neural Networks via Augmented Direct Feedback Alignment Yongbo Zhang Katsuma Inoue M. Nakajima Toshikazu Hashimoto Yasuo Kuniyoshi Kohei Nakajima 24 0 0 12 Sep 2024
Forward Learning of Graph Neural Networks Namyong Park Xing Wang Antoine Simoulin Shuai Yang Grey Yang Ryan Rossi Puja Trivedi Nesreen K. Ahmed GNN 41 1 0 16 Mar 2024
Random Feedback Alignment Algorithms to train Neural Networks: Why do they Align? Dominique F. Chu Florian Bacho ODL 17 0 0 04 Jun 2023
Learning with augmented target information: An alternative theory of Feedback Alignment Huzi Cheng Joshua W. Brown CVBM 8 0 0 03 Apr 2023
Biologically Plausible Learning on Neuromorphic Hardware Architectures Christopher Wolters Brady Taylor Edward Hanson Xiaoxuan Yang Ulf Schlichtmann Yiran Chen 6 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
Scaling Laws Beyond Backpropagation Matthew J. Filipovich Alessandro Cappelli Daniel Hesslow Julien Launay 19 3 0 26 Oct 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 13 28 0 31 Jan 2022
Convergence Analysis and Implicit Regularization of Feedback Alignment for Deep Linear Networks M. Girotti Ioannis Mitliagkas Gauthier Gidel 12 1 0 20 Oct 2021
Applications of the Free Energy Principle to Machine Learning and Neuroscience Beren Millidge DRL 20 7 0 30 Jun 2021
Credit Assignment in Neural Networks through Deep Feedback Control Alexander Meulemans Matilde Tristany Farinha Javier García Ordónez Pau Vilimelis Aceituno João Sacramento Benjamin Grewe 20 34 0 15 Jun 2021
Credit Assignment Through Broadcasting a Global Error Vector David G. Clark L. F. Abbott SueYeon Chung 17 23 0 08 Jun 2021
Bottom-up and top-down approaches for the design of neuromorphic processing systems: Tradeoffs and synergies between natural and artificial intelligence Charlotte Frenkel D. Bol Giacomo Indiveri 23 33 0 02 Jun 2021
Training Deep Architectures Without End-to-End Backpropagation: A Survey on the Provably Optimal Methods Shiyu Duan José C. Príncipe MQ 20 3 0 09 Jan 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
Align, then memorise: the dynamics of learning with feedback alignment Maria Refinetti Stéphane dÁscoli Ruben Ohana Sebastian Goldt 26 36 0 24 Nov 2020
Investigating the Scalability and Biological Plausibility of the Activation Relaxation Algorithm Beren Millidge Alexander Tschantz A. Seth Christopher L. Buckley 12 0 0 13 Oct 2020
A Theoretical Framework for Target Propagation Alexander Meulemans Francesco S. Carzaniga Johan A. K. Suykens João Sacramento Benjamin Grewe AAML 25 77 0 25 Jun 2020
Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures Julien Launay Iacopo Poli Franccois Boniface Florent Krzakala 27 62 0 23 Jun 2020
Learning without feedback: Fixed random learning signals allow for feedforward training of deep neural networks Charlotte Frenkel M. Lefebvre D. Bol 8 23 0 03 Sep 2019