Direct Feedback Alignment Provides Learning in Deep Neural Networks

6 September 2016

Papers citing "Direct Feedback Alignment Provides Learning in Deep Neural Networks"

50 / 248 papers shown

Title
ADMM-Based Training for Spiking Neural Networks Giovanni Perin Cesare Bidini Riccardo Mazzieri M. Rossi 34 0 0 08 May 2025
Can Local Representation Alignment RNNs Solve Temporal Tasks? Nikolay Manchev Luis C. Garcia-Peraza-Herrera AI4TS 43 0 0 18 Apr 2025
Toward Spiking Neural Network Local Learning Modules Resistant to Adversarial Attacks Jiaqi Lin Abhronil Sengupta AAML 31 0 0 11 Apr 2025
Forward Learning with Differential Privacy Mingqian Feng Zeliang Zhang Jinyang Jiang Yijie Peng Chenliang Xu 47 0 0 01 Apr 2025
Fast Training of Recurrent Neural Networks with Stationary State Feedbacks Paul Caillon Erwan Fagnou Alexandre Allauzen 39 0 0 29 Mar 2025
Multiplicative Learning Han Kim Hyungjoon Soh V. Periwal Junghyo Jo 55 0 0 13 Mar 2025
Training Large Neural Networks With Low-Dimensional Error Feedback Maher Hanut Jonathan Kadmon 47 1 0 27 Feb 2025
Blending Optimal Control and Biologically Plausible Learning for Noise-Robust Physical Neural Networks S. Sunada T. Niiyama Kazutaka Kanno Rin Nogami André Röhm Takato Awano Atsushi Uchida AI4CE 78 1 0 26 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 132 5 0 17 Feb 2025
TESS: A Scalable Temporally and Spatially Local Learning Rule for Spiking Neural Networks M. Apolinario Kaushik Roy Charlotte Frenkel 108 0 0 03 Feb 2025
Self-Assembly of a Biologically Plausible Learning Circuit Q. Liao Liu Ziyin Yulu Gan Brian Cheung Mark Harnett Tomaso Poggio 57 0 0 31 Dec 2024
TIFeD: a Tiny Integer-based Federated learning algorithm with Direct feedback alignment Luca Colombo Alessandro Falcetta Manuel Roveri FedML 108 3 0 25 Nov 2024
Poor Man's Training on MCUs: A Memory-Efficient Quantized Back-Propagation-Free Approach Yequan Zhao Hai Li Ian Young Zheng-Wei Zhang MQ 39 2 0 07 Nov 2024
Protecting Feed-Forward Networks from Adversarial Attacks Using Predictive Coding Ehsan Ganjidoost Jeff Orchard AAML 32 0 0 31 Oct 2024
Beyond Backpropagation: Optimization with Multi-Tangent Forward Gradients Katharina Flügel D. Coquelin Marie Weiel Achim Streit Markus Gotz 27 0 0 23 Oct 2024
FLOPS: Forward Learning with OPtimal Sampling Tao Ren Zishi Zhang Jinyang Jiang Guanghao Li Zeliang Zhang Mingqian Feng Yijie Peng 42 1 0 08 Oct 2024
Replacement Learning: Training Vision Tasks with Fewer Learnable Parameters Yuming Zhang Peizhe Wang Shouxin Zhang Dongzhi Guan Jiabin Liu Junhao Su 40 0 0 02 Oct 2024
Counter-Current Learning: A Biologically Plausible Dual Network Approach for Deep Learning Chia-Hsiang Kao Bharath Hariharan 56 1 0 30 Sep 2024
Unifying back-propagation and forward-forward algorithms through model predictive control Lianhai Ren Qianxiao Li 36 1 0 29 Sep 2024
Is All Learning (Natural) Gradient Descent? Lucas Shoji Kenta Suzuki Leo Kozachkov 35 1 0 24 Sep 2024
Novel Saliency Analysis for the Forward Forward Algorithm Mitra Bakhshi 34 1 0 18 Sep 2024
Memory Networks: Towards Fully Biologically Plausible Learning Jacobo Ruiz Manas Gupta 30 0 0 18 Sep 2024
Self-Contrastive Forward-Forward Algorithm Xing Chen Dongshu Liu Jérémie Laydevant Julie Grollier 46 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 43 0 0 12 Sep 2024
Distance-Forward Learning: Enhancing the Forward-Forward Algorithm Towards High-Performance On-Chip Learning Yujie Wu Siyuan Xu Jibin Wu Lei Deng Mingkun Xu Qinghao Wen Guoqi Li FedML 33 3 0 27 Aug 2024
When In-memory Computing Meets Spiking Neural Networks -- A Perspective on Device-Circuit-System-and-Algorithm Co-design Abhishek Moitra Abhiroop Bhattacharjee Yuhang Li Youngeun Kim Priyadarshini Panda 32 1 0 22 Aug 2024
Online Pseudo-Zeroth-Order Training of Neuromorphic Spiking Neural Networks Mingqing Xiao Qingyan Meng Zongpeng Zhang D.K. He Zhouchen Lin 45 0 0 17 Jul 2024
Correlations Are Ruining Your Gradient Descent Nasir Ahmad 52 3 0 15 Jul 2024
Learning by the F-adjoint Ahmed Boughammoura FedML 29 0 0 08 Jul 2024
HPFF: Hierarchical Locally Supervised Learning with Patch Feature Fusion Junhao Su Chenghao He Feiyu Zhu Xiaojie Xu Dongzhi Guan Chenyang Si 58 2 0 08 Jul 2024
Momentum Auxiliary Network for Supervised Local Learning Junhao Su Changpeng Cai Feiyu Zhu Chenghao He Xiaojie Xu Dongzhi Guan Chenyang Si 46 4 0 08 Jul 2024
MLAAN: Scaling Supervised Local Learning with Multilaminar Leap Augmented Auxiliary Network Yuming Zhang Shouxin Zhang Peizhe Wang Feiyu Zhu Dongzhi Guan Junhao Su Jiabin Liu Changpeng Cai 33 2 0 24 Jun 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
Online Training of Hopfield Networks using Predictive Coding Ehsan Ganjidoost Mallory A. Snow Jeff Orchard 28 0 0 20 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 42 2 0 07 Jun 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 56 10 0 05 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 230 1 0 27 May 2024
LLS: Local Learning Rule for Deep Neural Networks Inspired by Neural Activity Synchronization M. Apolinario Arani Roy Kaushik Roy 43 2 0 24 May 2024
Contribute to balance, wire in accordance: Emergence of backpropagation from a simple, bio-plausible neuroplasticity rule Xinhao Fan S. P. Mysore 39 0 0 23 May 2024
Gradient-Free Training of Recurrent Neural Networks using Random Perturbations Jesus Garcia Fernandez Sander Keemink Marcel van Gerven AAML 47 4 0 14 May 2024
Lightweight Inference for Forward-Forward Algorithm Amin Aminifar Baichuan Huang Azra Abtahi Amir Aminifar 35 3 0 08 Apr 2024
Thermal Crosstalk Modelling and Compensation Methods for Programmable Photonic Integrated Circuits Isidora Teofilović A. Cem David Sanchez-Jacome Daniel Pérez-López Francesco Da Ros 39 2 0 19 Mar 2024
Approximated Likelihood Ratio: A Forward-Only and Parallel Framework for Boosting Neural Network Training Zeliang Zhang Jinyang Jiang Zhuo Liu Susan Liang Yijie Peng Chenliang Xu 42 0 0 18 Mar 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 47 1 0 16 Mar 2024
Scaling Supervised Local Learning with Augmented Auxiliary Networks Chenxiang Ma Jibin Wu Chenyang Si Kay Chen Tan 49 2 0 27 Feb 2024
Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks Mingqing Xiao Qingyan Meng Zongpeng Zhang D.K. He Zhouchen Lin CLL 31 7 0 19 Feb 2024
A Review of Neuroscience-Inspired Machine Learning Alexander Ororbia A. Mali Adam Kohan Beren Millidge Tommaso Salvatori 37 7 0 16 Feb 2024
End-to-End Training Induces Information Bottleneck through Layer-Role Differentiation: A Comparative Analysis with Layer-wise Training Keitaro Sakamoto Issei Sato 24 4 0 14 Feb 2024
Two Tales of Single-Phase Contrastive Hebbian Learning R. Høier Christopher Zach 35 1 0 13 Feb 2024