Spiking Neural Network

Spiking neural networks (SNNs), inspired by the brain's event-driven communication, aim to create energy-efficient artificial intelligence by processing information through binary spikes rather than continuous values. Current research emphasizes improving training efficiency through novel neuron models (e.g., parallel resonate and fire neurons, multi-compartment neurons), developing specialized weight initialization methods, and exploring various coding schemes (e.g., Poisson coding, stepwise weighted spike coding) to optimize performance and reduce energy consumption. This field is significant due to SNNs' potential for low-power applications in embedded systems, neuromorphic computing, and real-time signal processing tasks like robotic manipulation and brain-computer interfaces.

Papers

May 20, 2023

Probabilistic Modeling: Proving the Lottery Ticket Hypothesis in Spiking Neural Network
Man Yao, Yuhong Chou, Guangshe Zhao, Xiawu Zheng, Yonghong Tian, Bo Xu, Guoqi Li
Spiking Neural Network Probabilistic Model Lottery Ticket Hypothesis

May 19, 2023

Dive into the Power of Neuronal Heterogeneity
Guobin Shen, Dongcheng Zhao, Yiting Dong, Yang Li, Yi Zeng
Spiking Neural Network Real Power DIVeR Identification Neuronal Heterogeneity

May 18, 2023

SPENSER: Towards a NeuroEvolutionary Approach for Convolutional Spiking Neural Networks
Henrique Branquinho, Nuno Lourenço, Ernesto Costa
Spiking Neural Network SNN Model Convolutional Spiking Neural Network Spike Based Backpropagation Grammatical Evolution

May 15, 2023

Neural information coding for efficient spike-based image denoising
Andrea Castagnetti, Alain Pegatoquet, Benoît Miramond
Spiking Neural Network Image Restoration Task Spike Stream Neural Information

May 13, 2023

Quantization in Spiking Neural Networks
Bernhard A. Moser, Michael Lunglmayr
Spiking Neural Network Quantization Operator Neuron Model Spike Train Leaky Integrate and Fire Based Reset

May 9, 2023

Spiking Neural Networks in the Alexiewicz Topology: A New Perspective on Analysis and Error Bounds
Bernhard A. Moser, Michael Lunglmayr
General Analysis Spiking Neural Network Neuromorphic Computing New Perspective Neuron Model Spike Train Error Bound Leaky Integrate and Fire Spherical Topology

May 3, 2023

Joint A-SNN: Joint Training of Artificial and Spiking Neural Networks via Self-Distillation and Weight Factorization
Yufei Guo, Weihang Peng, Yuanpei Chen, Liwen Zhang, Xiaode Liu, Xuhui Huang, Zhe Ma
Neural Network Spiking Neural Network Self Distillation Synthetic to Real Joint Training Binary Spike Weight Factorization

April 30, 2023

Sparsifying Spiking Networks through Local Rhythms
Wilkie Olin-Ammentorp
Neural Network Spiking Neural Network Computation Method Spike Protein Novel Application Conventional Neural Network R Theta Local Neighborhood Pattern

April 27, 2023

Spiking Neural Network Decision Feedback Equalization for IM/DD Systems
Alexander von Bank, Eike-Manuel Edelmann, Laurent Schmalen
Neural Network Spiking Neural Network Spiking Neuron Parametric Equalizer

April 26, 2023

Membrane Potential Distribution Adjustment and Parametric Surrogate Gradient in Spiking Neural Networks
Siqi Wang, Tee Hiang Cheng, Meng-Hiot Lim
Spiking Neural Network Surrogate Gradient Membrane Potential

April 25, 2023

April 24, 2023

Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration
Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen, Caiwen Ding
Spiking Neural Network Tiny ImageNet SNN Model Set Prediction 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 20, 2023

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 14, 2023

A Bibliometric Review of Neuromorphic Computing and Spiking Neural Networks
Nicholas J. Pritchard, Andreas Wicenec, Mohammed Bennamoun, Richard Dodson
Spiking Neural Network Neuromorphic Computing Neuromorphic Hardware Low Power Computational Power Bibliometric Analysis Three Layer Neural Network

April 13, 2023

Temporal Knowledge Sharing enable Spiking Neural Network Learning from Past and Future
Yiting Dong, Dongcheng Zhao, Yi Zeng
Spiking Neural Network Future Reasoning Self Distillation Neuromorphic Datasets Brain Like Temporal Domain Generalization

April 10, 2023

Stochastic Domain Wall-Magnetic Tunnel Junction Artificial Neurons for Noise-Resilient Spiking Neural Networks
Thomas Leonard, Samuel Liu, Harrison Jin, Jean Anne C. Incorvia
Spiking Neural Network Neuromorphic Computing Magnetic Tunnel Junction

Spiking Neural Network

Papers

Probabilistic Modeling: Proving the Lottery Ticket Hypothesis in Spiking Neural Network

Dive into the Power of Neuronal Heterogeneity

SPENSER: Towards a NeuroEvolutionary Approach for Convolutional Spiking Neural Networks

Neural information coding for efficient spike-based image denoising

Quantization in Spiking Neural Networks

Spiking Neural Networks in the Alexiewicz Topology: A New Perspective on Analysis and Error Bounds

Joint A-SNN: Joint Training of Artificial and Spiking Neural Networks via Self-Distillation and Weight Factorization

Sparsifying Spiking Networks through Local Rhythms

Spiking Neural Network Decision Feedback Equalization for IM/DD Systems

Membrane Potential Distribution Adjustment and Parametric Surrogate Gradient in Spiking Neural Networks

Uncovering the Representation of Spiking Neural Networks Trained with Surrogate Gradient

Parallel Spiking Neurons with High Efficiency and Ability to Learn Long-term Dependencies

Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration

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

Spiking-Fer: Spiking Neural Network for Facial Expression Recognition With Event Cameras

Efficient Uncertainty Estimation in Spiking Neural Networks via MC-dropout

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

A Bibliometric Review of Neuromorphic Computing and Spiking Neural Networks

Temporal Knowledge Sharing enable Spiking Neural Network Learning from Past and Future

Stochastic Domain Wall-Magnetic Tunnel Junction Artificial Neurons for Noise-Resilient Spiking Neural Networks