How Important is Weight Symmetry in Backpropagation?

17 October 2015

Papers citing "How Important is Weight Symmetry in Backpropagation?"

50 / 91 papers shown

Title
Training Large Neural Networks With Low-Dimensional Error Feedback Maher Hanut Jonathan Kadmon 45 1 0 27 Feb 2025
Sign-Symmetry Learning Rules are Robust Fine-Tuners Aymene Berriche Mehdi Zakaria Adjal Riyadh Baghdadi AAML 52 0 0 09 Feb 2025
Self-Assembly of a Biologically Plausible Learning Circuit Q. Liao Liu Ziyin Yulu Gan Brian Cheung Mark Harnett Tomaso Poggio 52 0 0 31 Dec 2024
Protecting Feed-Forward Networks from Adversarial Attacks Using Predictive Coding Ehsan Ganjidoost Jeff Orchard AAML 32 3 0 31 Oct 2024
Oja's plasticity rule overcomes several challenges of training neural networks under biological constraints Navid Shervani-Tabar Marzieh Alireza Mirhoseini Robert Rosenbaum AAML AI4CE 45 0 0 15 Aug 2024
Online Pseudo-Zeroth-Order Training of Neuromorphic Spiking Neural Networks Mingqing Xiao Qingyan Meng Zongpeng Zhang D.K. He Zhouchen Lin 40 0 0 17 Jul 2024
Towards Biologically Plausible Computing: A Comprehensive Comparison Changze Lv Yufei Gu Zhengkang Guo Zhibo Xu Yixin Wu ... Tianlong Li Jianhao Zhu Cenyuan Zhang Zixuan Ling Xiaoqing Zheng 38 1 0 23 Jun 2024
Towards Interpretable Deep Local Learning with Successive Gradient Reconciliation Yibo Yang Xiaojie Li Motasem Alfarra Hasan Hammoud Adel Bibi Philip Torr Guohao Li 37 2 0 07 Jun 2024
Deep Learning without Weight Symmetry Ji-An Li M. Benna 32 1 0 31 May 2024
Pretraining with Random Noise for Fast and Robust Learning without Weight Transport Jeonghwan Cheon Sang Wan Lee Se-Bum Paik OOD 203 1 0 27 May 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
Lightweight Inference for Forward-Forward Algorithm Amin Aminifar Baichuan Huang Azra Abtahi Amir Aminifar 35 3 0 08 Apr 2024
NeuroFlux: Memory-Efficient CNN Training Using Adaptive Local Learning Dhananjay Saikumar Blesson Varghese 24 1 0 21 Feb 2024
A Review of Neuroscience-Inspired Machine Learning Alexander Ororbia A. Mali Adam Kohan Beren Millidge Tommaso Salvatori 29 7 0 16 Feb 2024
Zenkai -- Framework For Exploring Beyond Backpropagation Greg Short 25 0 0 16 Nov 2023
Brain-like Flexible Visual Inference by Harnessing Feedback-Feedforward Alignment Tahereh Toosi Elias B. Issa 19 2 0 31 Oct 2023
Improving equilibrium propagation without weight symmetry through Jacobian homeostasis Axel Laborieux Friedemann Zenke 20 7 0 05 Sep 2023
Can Forward Gradient Match Backpropagation? Louis Fournier Stéphane Rivaud Eugene Belilovsky Michael Eickenberg Edouard Oyallon 19 16 0 12 Jun 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
Implicit Regularization in Feedback Alignment Learning Mechanisms for Neural Networks Zachary Robertson Oluwasanmi Koyejo 38 0 0 02 Jun 2023
Synaptic Weight Distributions Depend on the Geometry of Plasticity Roman Pogodin Jonathan H. Cornford Arna Ghosh Gauthier Gidel Guillaume Lajoie Blake A. Richards 23 4 0 30 May 2023
Understanding and Improving Optimization in Predictive Coding Networks Nick Alonso J. Krichmar Emre Neftci 73 7 0 23 May 2023
Feed-Forward Optimization With Delayed Feedback for Neural Networks Katharina Flügel D. Coquelin Marie Weiel Charlotte Debus Achim Streit Markus Goetz AI4CE 40 7 0 26 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 27 15 0 10 Feb 2023
Interpreting learning in biological neural networks as zero-order optimization method Johannes Schmidt-Hieber 30 4 0 27 Jan 2023
Meta-Learning Biologically Plausible Plasticity Rules with Random Feedback Pathways Navid Shervani-Tabar Robert Rosenbaum AI4CE 42 14 0 28 Oct 2022
Scaling Forward Gradient With Local Losses Mengye Ren Simon Kornblith Renjie Liao Geoffrey E. Hinton 81 49 0 07 Oct 2022
The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks Blake Bordelon Cengiz Pehlevan 41 22 0 05 Oct 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
A Computational Framework of Cortical Microcircuits Approximates Sign-concordant Random Backpropagation Yukun Yang Peng Li 24 1 0 15 May 2022
Signal Propagation: A Framework for Learning and Inference In a Forward Pass Adam A. Kohan E. Rietman H. Siegelmann 19 26 0 04 Apr 2022
Deep Layer-wise Networks Have Closed-Form Weights Chieh-Tsai Wu A. Masoomi Arthur Gretton Jennifer Dy 29 3 0 01 Feb 2022
Error-driven Input Modulation: Solving the Credit Assignment Problem without a Backward Pass Giorgia Dellaferrera Gabriel Kreiman 29 53 0 27 Jan 2022
Information Bottleneck-Based Hebbian Learning Rule Naturally Ties Working Memory and Synaptic Updates Kyle Daruwalla Mikko H. Lipasti 15 0 0 24 Nov 2021
Biologically Plausible Training Mechanisms for Self-Supervised Learning in Deep Networks Mufeng Tang Yibo Yang Y. Amit SSL 16 7 0 30 Sep 2021
BioLCNet: Reward-modulated Locally Connected Spiking Neural Networks Hafez Ghaemi Erfan Mirzaei Mahbod Nouri Saeed Reza Kheradpisheh 16 2 0 12 Sep 2021
Benchmarking the Accuracy and Robustness of Feedback Alignment Algorithms Albert Jiménez Sanfiz Mohamed Akrout OOD AAML 14 8 0 30 Aug 2021
Tourbillon: a Physically Plausible Neural Architecture Mohammadamin Tavakoli Peter Sadowski Pierre Baldi 29 0 0 13 Jul 2021
Applications of the Free Energy Principle to Machine Learning and Neuroscience Beren Millidge DRL 20 7 0 30 Jun 2021
How to Train Your Wide Neural Network Without Backprop: An Input-Weight Alignment Perspective Akhilan Boopathy Ila Fiete 39 9 0 15 Jun 2021
The Backpropagation Algorithm Implemented on Spiking Neuromorphic Hardware Alpha Renner F. Sheldon Anatoly Zlotnik L. Tao A. Sornborger 21 36 0 13 Jun 2021
Credit Assignment Through Broadcasting a Global Error Vector David G. Clark L. F. Abbott SueYeon Chung 25 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 34 33 0 02 Jun 2021
Efficient Training Convolutional Neural Networks on Edge Devices with Gradient-pruned Sign-symmetric Feedback Alignment Ziyang Hong C. Yue 26 2 0 04 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
Training DNNs in O(1) memory with MEM-DFA using Random Matrices Tien Chu Kamil Mykitiuk Miron Szewczyk Adam Wiktor Z. Wojna 15 2 0 21 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
Kernel Dependence Network Chieh-Tsai Wu A. Masoomi Arthur Gretton Jennifer Dy 8 0 0 04 Nov 2020
Identifying Learning Rules From Neural Network Observables Aran Nayebi S. Srivastava Surya Ganguli Daniel L. K. Yamins 8 21 0 22 Oct 2020
Understanding Information Processing in Human Brain by Interpreting Machine Learning Models Ilya Kuzovkin HAI 10 2 0 17 Oct 2020