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"

7 / 7 papers shown

Title
Open the box of digital neuromorphic processor: Towards effective algorithm-hardware co-design Guangzhi Tang A. Safa K. Shidqi Paul Detterer Stefano Traferro Mario Konijnenburg Manolis Sifalakis Gert-Jan van Schaik Amirreza Yousefzadeh 27 11 0 27 Mar 2023
Intelligence Processing Units Accelerate Neuromorphic Learning P. Sun A. Titterton Anjlee Gopiani Tim Santos A. Basu Wei D. Lu Jason Eshraghian 9 8 0 19 Nov 2022
Desire Backpropagation: A Lightweight Training Algorithm for Multi-Layer Spiking Neural Networks based on Spike-Timing-Dependent Plasticity Daniel Gerlinghoff Tao Luo Rick Siow Mong Goh Weng-Fai Wong 14 2 0 10 Nov 2022
Deep Reinforcement Learning with Population-Coded Spiking Neural Network for Continuous Control Guangzhi Tang Neelesh Kumar Raymond Yoo Konstantinos Michmizos 52 74 0 19 Oct 2020
Long short-term memory and learning-to-learn in networks of spiking neurons G. Bellec Darjan Salaj Anand Subramoney Robert Legenstein Wolfgang Maass 119 481 0 26 Mar 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 338 11,684 0 09 Mar 2017
Neuromorphic Deep Learning Machines Emre Neftci C. Augustine Somnath Paul Georgios Detorakis BDL 129 257 0 16 Dec 2016