Deep Spiking Neural Network

Deep Spiking Neural Networks (DSNNs) are a class of artificial neural networks designed to mimic the biological function of neurons using binary spike signals, offering potential advantages in energy efficiency and temporal information processing compared to traditional artificial neural networks. Current research focuses on improving DSNN training methods (e.g., through surrogate gradients and knowledge distillation from ANNs), enhancing efficiency via compression techniques (pruning, quantization), and exploring novel architectures inspired by biological neural pathways. These advancements aim to overcome limitations in accuracy and scalability, paving the way for DSNN deployment in resource-constrained applications and furthering our understanding of biological neural computation.

Papers

November 11, 2024

Evolving Efficient Genetic Encoding for Deep Spiking Neural Networks
Wenxuan Pan, Feifei Zhao, Bing Han, Haibo Tong, Yi Zeng
Neural Network Neural Code Deep Spiking Neural Network Synthetic DNA

October 15, 2024

Advancing Training Efficiency of Deep Spiking Neural Networks through Rate-based Backpropagation
Chengting Yu, Lei Liu, Gaoang Wang, Erping Li, Aili Wang
Spiking Neural Network Efficient Training Deep Spiking Neural Network

September 28, 2024

Membership Privacy Evaluation in Deep Spiking Neural Networks
Jiaxin Li, Gorka Abad, Stjepan Picek, Mauro Conti
Neural Network Spiking Neural Network Neuromorphic Datasets Membership Privacy Deep Spiking Neural Network

August 30, 2024

Stepwise Weighted Spike Coding for Deep Spiking Neural Networks
Yiwen Gu, Junchuan Gu, Haibin Shen, Kejie Huang
Spiking Neural Network Neuron Model Neural Computation Spike Encoding Deep Spiking Neural Network

June 3, 2024

August 1, 2023

Gradient Scaling on Deep Spiking Neural Networks with Spike-Dependent Local Information
Seongsik Park, Jeonghee Jo, Jongkil Park, Yeonjoo Jeong, Jaewook Kim, Suyoun Lee, Joon Young Kwak, Inho Kim, Jong-Keuk Park, Kyeong Seok Lee, Gye Weon Hwang, Hyun Jae Jang
Spatio Temporal Spike Protein Deep Spiking Neural Network Gradient Scaling

May 31, 2023

Direct Learning-Based Deep Spiking Neural Networks: A Review
Yufei Guo, Xuhui Huang, Zhe Ma
Narrative Review Brain Inspired Binary Spike Deep Spiking Neural Network

April 21, 2023

Multi-scale Evolutionary Neural Architecture Search for Deep Spiking Neural Networks
Wenxuan Pan, Feifei Zhao, Guobin Shen, Yi Zeng
Neural Architecture Search Spiking Neural Network Neuromorphic Datasets Brain Inspired Deep Spiking Neural Network Neural Motif

April 17, 2023

LaSNN: Layer-wise ANN-to-SNN Distillation for Effective and Efficient Training in Deep Spiking Neural Networks
Di Hong, Jiangrong Shen, Yu Qi, Yueming Wang
Spiking Neural Network Efficient Training Deep Spiking Neural Network Layer Wise Distillation

April 12, 2023

Constructing Deep Spiking Neural Networks from Artificial Neural Networks with Knowledge Distillation
Qi Xu, Yaxin Li, Jiangrong Shen, Jian K Liu, Huajin Tang, Gang Pan
Neural Network Knowledge Distillation Spike Train SNN Based Brain Inspired Computing Deep Spiking Neural Network Student GNN

March 9, 2023

Deep Spiking Neural Networks with High Representation Similarity Model Visual Pathways of Macaque and Mouse
Liwei Huang, Zhengyu Ma, Liutao Yu, Huihui Zhou, Yonghong Tian
Neural Representation Brain Inspired Deep Spiking Neural Network Mouse Data Visual Pathway

September 24, 2022

Spiking SiamFC++: Deep Spiking Neural Network for Object Tracking
Shuiying Xiang, Tao Zhang, Shuqing Jiang, Yanan Han, Yahui Zhang, Chenyang Du, Xingxing Guo, Licun Yu, Yuechun Shi, Yue Hao
Neural Network Spiking Neural Network Siamese Network Deep Spiking Neural Network

August 9, 2022

A Time-to-first-spike Coding and Conversion Aware Training for Energy-Efficient Deep Spiking Neural Network Processor Design
Dongwoo Lew, Kyungchul Lee, Jongsun Park
State of the Art Programming Assistance Energy Efficient Spike Timing SNN Conversion Deep Spiking Neural Network Conversion Rate Prediction

April 20, 2022

Axonal Delay As a Short-Term Memory for Feed Forward Deep Spiking Neural Networks
Pengfei Sun, Longwei Zhu, Dick Botteldooren
Neuromorphic Datasets Short Term Memory Spike Timing Synaptic Delay Biological Neuron Deep Spiking Neural Network

Deep Spiking Neural Network

Papers

Evolving Efficient Genetic Encoding for Deep Spiking Neural Networks

Advancing Training Efficiency of Deep Spiking Neural Networks through Rate-based Backpropagation

Membership Privacy Evaluation in Deep Spiking Neural Networks

Stepwise Weighted Spike Coding for Deep Spiking Neural Networks

Toward Efficient Deep Spiking Neuron Networks:A Survey On Compression

Towards Efficient Deep Spiking Neural Networks Construction with Spiking Activity based Pruning

Gradient Scaling on Deep Spiking Neural Networks with Spike-Dependent Local Information

Direct Learning-Based Deep Spiking Neural Networks: A Review

Multi-scale Evolutionary Neural Architecture Search for Deep Spiking Neural Networks

LaSNN: Layer-wise ANN-to-SNN Distillation for Effective and Efficient Training in Deep Spiking Neural Networks

Constructing Deep Spiking Neural Networks from Artificial Neural Networks with Knowledge Distillation

Deep Spiking Neural Networks with High Representation Similarity Model Visual Pathways of Macaque and Mouse

Spiking SiamFC++: Deep Spiking Neural Network for Object Tracking

A Time-to-first-spike Coding and Conversion Aware Training for Energy-Efficient Deep Spiking Neural Network Processor Design

Axonal Delay As a Short-Term Memory for Feed Forward Deep Spiking Neural Networks