BioGrad: Biologically Plausible Gradient-Based Learning for Spiking Neural Networks

27 October 2021

Papers citing "BioGrad: Biologically Plausible Gradient-Based Learning for Spiking Neural Networks"

9 / 9 papers shown

Title
Deep Reinforcement Learning with Population-Coded Spiking Neural Network for Continuous Control Guangzhi Tang Neelesh Kumar Raymond Yoo Konstantinos Michmizos 82 75 0 19 Oct 2020
Event-Driven Visual-Tactile Sensing and Learning for Robots Tasbolat Taunyazov Weicong Sng H. See Brian Z. H. Lim Jethro Kuan Abdul Fatir Ansari Benjamin C. K. Tee Harold Soh 39 92 0 15 Sep 2020
Spike-based causal inference for weight alignment Jordan Guerguiev Konrad Paul Kording Blake A. Richards CML 45 23 0 03 Oct 2019
Continual Learning for Robotics: Definition, Framework, Learning Strategies, Opportunities and Challenges Timothée Lesort Vincenzo Lomonaco Andrei Stoian Davide Maltoni David Filliat Natalia Díaz Rodríguez CLL 56 249 0 29 Jun 2019
Rapid online learning and robust recall in a neuromorphic olfactory circuit N. Imam T. A. Cleland 39 142 0 17 Jun 2019
Long short-term memory and learning-to-learn in networks of spiking neurons G. Bellec Darjan Salaj Anand Subramoney Robert Legenstein Wolfgang Maass 135 484 0 26 Mar 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 759 11,793 0 09 Mar 2017
Convolutional Networks for Fast, Energy-Efficient Neuromorphic Computing S. K. Esser P. Merolla John V. Arthur A. Cassidy R. Appuswamy ... Pallab Datta A. Amir B. Taba M. Flickner D. Modha 3DH 48 715 0 28 Mar 2016
Practical recommendations for gradient-based training of deep architectures Yoshua Bengio 3DH ODL 146 2,195 0 24 Jun 2012