Efficient training of spiking neural networks with temporally-truncated local backpropagation through time

Efficient training of spiking neural networks with temporally-truncated local backpropagation through time

Directly training spiking neural networks (SNNs) has remained challenging due to complex neural dynamics and intrinsic non-differentiability in firing functions. The well-known backpropagation through time (BPTT) algorithm proposed to train SNNs suffers from large memory footprint and prohibits back...

Full description

Bibliographic Details
Main Authors:	Wenzhe Guo, Mohammed E. Fouda, Ahmed M. Eltawil, Khaled Nabil Salama
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2023-04-01
Series:	Frontiers in Neuroscience
Subjects:	backpropagation through time deep learning energy-efficient training local learning neuromorphic computing spiking neural networks
Online Access:	https://www.frontiersin.org/articles/10.3389/fnins.2023.1047008/full

Similar Items

Unsupervised Adaptive Weight Pruning for Energy-Efficient Neuromorphic Systems
by: Wenzhe Guo, et al.
Published: (2020-11-01)

Neural Coding in Spiking Neural Networks: A Comparative Study for Robust Neuromorphic Systems
by: Wenzhe Guo, et al.
Published: (2021-03-01)

Training Deep Spiking Neural Networks using Backpropagation
by: Jun Haeng Lee, et al.
Published: (2016-11-01)

Towards Efficient Neuromorphic Hardware: Unsupervised Adaptive Neuron Pruning
by: Wenzhe Guo, et al.
Published: (2020-06-01)

EXODUS: Stable and efficient training of spiking neural networks
by: Felix C. Bauer, et al.
Published: (2023-02-01)

SSTDP: Supervised Spike Timing Dependent Plasticity for Efficient Spiking Neural Network Training
by: Fangxin Liu, et al.
Published: (2021-11-01)

Backpropagation With Sparsity Regularization for Spiking Neural Network Learning
by: Yulong Yan, et al.
Published: (2022-04-01)

Spike-Train Level Direct Feedback Alignment: Sidestepping Backpropagation for On-Chip Training of Spiking Neural Nets
by: Jeongjun Lee, et al.
Published: (2020-03-01)

Enabling Spike-Based Backpropagation for Training Deep Neural Network Architectures
by: Chankyu Lee, et al.
Published: (2020-02-01)

On-Chip Training Spiking Neural Networks Using Approximated Backpropagation With Analog Synaptic Devices
by: Dongseok Kwon, et al.
Published: (2020-07-01)

Event-Based Optical Flow Estimation with Spatio-Temporal Backpropagation Trained Spiking Neural Network
by: Yisa Zhang, et al.
Published: (2023-01-01)

Bayesian continual learning via spiking neural networks
by: Nicolas Skatchkovsky, et al.
Published: (2022-11-01)

VTSNN: a virtual temporal spiking neural network
by: Xue-Rui Qiu, et al.
Published: (2023-05-01)

SpikePropamine: Differentiable Plasticity in Spiking Neural Networks
by: Samuel Schmidgall, et al.
Published: (2021-09-01)

Spatio-Temporal Backpropagation for Training High-Performance Spiking Neural Networks
by: Yujie Wu, et al.
Published: (2018-05-01)

A temporally and spatially local spike-based backpropagation algorithm to enable training in hardware
by: Anmol Biswas, et al.
Published: (2023-01-01)

Design of Fully Analogue Artificial Neural Network with Learning Based on Backpropagation
by: F. Paulu, et al.
Published: (2021-06-01)

Direct Training via Backpropagation for Ultra-Low-Latency Spiking Neural Networks with Multi-Threshold
by: Changqing Xu, et al.
Published: (2022-09-01)

A Sparsity-Driven Backpropagation-Less Learning Framework Using Populations of Spiking Growth Transform Neurons
by: Ahana Gangopadhyay, et al.
Published: (2021-07-01)

Dynamic layer-span connecting spiking neural networks with backpropagation training
by: Zijjian Wang, et al.
Published: (2023-10-01)

Spiking Neural Networks for Computational Intelligence: An Overview
by: Shirin Dora, et al.
Published: (2021-11-01)

Efficient Spiking Neural Networks With Logarithmic Temporal Coding
by: Ming Zhang, et al.
Published: (2020-01-01)

Speculative Backpropagation for CNN Parallel Training
by: Sangwoo Park, et al.
Published: (2020-01-01)

Supervised Learning With First-to-Spike Decoding in Multilayer Spiking Neural Networks
by: Brian Gardner, et al.
Published: (2021-04-01)

An Optimized Deep Spiking Neural Network Architecture Without Gradients
by: Yeshwanth Bethi, et al.
Published: (2022-01-01)

Supervised Learning in All FeFET-Based Spiking Neural Network: Opportunities and Challenges
by: Sourav Dutta, et al.
Published: (2020-06-01)

A new backpropagation neural network classification model for prediction of incidence of malaria
by: Ajeet Kumar Verma, et al.
Published: (2020-01-01)

Spiking Autoencoders With Temporal Coding
by: Iulia-Maria Comşa, et al.
Published: (2021-08-01)

Hardware-Efficient On-line Learning through Pipelined Truncated-Error Backpropagation in Binary-State Networks
by: Hesham Mostafa, et al.
Published: (2017-09-01)

Neuroevolution Guided Hybrid Spiking Neural Network Training
by: Sen Lu, et al.
Published: (2022-04-01)

Continual Learning With Speculative Backpropagation and Activation History
by: Sangwoo Park, et al.
Published: (2022-01-01)

Implementation of Field-Programmable Gate Array Platform for Object Classification Tasks Using Spike-Based Backpropagated Deep Convolutional Spiking Neural Networks
by: Vijay Kakani, et al.
Published: (2023-06-01)

NESIM-RT: A real-time distributed spiking neural network simulator
by: Daniel J. Rosa-Gallardo, et al.
Published: (2023-05-01)

Neuromorphic Tactile Edge Orientation Classification in an Unsupervised Spiking Neural Network
by: Fraser L. A. Macdonald, et al.
Published: (2022-09-01)

BPLC + NOSO: backpropagation of errors based on latency code with neurons that only spike once at most
by: Seong Min Jin, et al.
Published: (2023-02-01)

Enhancing spiking neural networks with hybrid top-down attention
by: Faqiang Liu, et al.
Published: (2022-08-01)

Predictive Analysis of Rice Pest Distribution in Bali Province Using Backpropagation Neural Network
by: I Kadek Agus Dwipayana, et al.
Published: (2023-07-01)

A Review of Recent Advances and Application for Spiking Neural Networks
by: Liu Hao, et al.
Published: (2023-12-01)

Editorial: Spiking Neural Network Learning, Benchmarking, Programming and Executing
by: Guoqi Li, et al.
Published: (2020-04-01)

A Circuit-Based Neural Network with Hybrid Learning of Backpropagation and Random Weight Change Algorithms
by: Changju Yang, et al.
Published: (2016-12-01)