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

January 8, 2024

Enhancing Adaptive History Reserving by Spiking Convolutional Block Attention Module in Recurrent Neural Networks
Qi Xu, Yuyuan Gao, Jiangrong Shen, Yaxin Li, Xuming Ran, Huajin Tang, Gang Pan
Recurrent Neural Network Spiking Neural Network Spatio Temporal Temporal Feature Convolutional Block Attention Convolutional Structure Loss Reserving

January 5, 2024

Training a General Spiking Neural Network with Improved Efficiency and Minimum Latency
Yunpeng Yao, Man Wu, Zheng Chen, Renyuan Zhang
High Efficiency Spiking Neural Network Energy Efficient Binary Spike High Performing Minimum Latency

January 4, 2024

Spikformer V2: Join the High Accuracy Club on ImageNet with an SNN Ticket
Zhaokun Zhou, Kaiwei Che, Wei Fang, Keyu Tian, Yuesheng Zhu, Shuicheng Yan, Yonghong Tian, Li Yuan
Supervised ImageNet Spiking Neural Network Spiking Transformer Convolutional Spiking Neural Network Accuracy on the Line Spikformer Architecture

January 2, 2024

December 28, 2023

SparseProp: Efficient Event-Based Simulation and Training of Sparse Recurrent Spiking Neural Networks
Rainer Engelken
Training Data High Efficiency Spiking Neural Network Simulation Study Neuron Model

December 26, 2023

December 24, 2023

Deep Pulse-Coupled Neural Networks
Zexiang Yi, Jing Lian, Yunliang Qi, Zhaofei Yu, Huajin Tang, Yide Ma, Jizhao Liu
Spiking Neural Network Pulse Coupled Neural Network

December 14, 2023

Learning Long Sequences in Spiking Neural Networks
Matei Ioan Stan, Oliver Rhodes
Recurrent Neural Network Spiking Neural Network State of the Art Neuromorphic Hardware Long Sequence Recurrent Neural Network Architecture Target Sequence

December 12, 2023

December 9, 2023

NiSNN-A: Non-iterative Spiking Neural Networks with Attention with Application to Motor Imagery EEG Classification
Chuhan Zhang, Wei Pan, Cosimo Della Santina
Application Proficiency Spiking Neural Network Human Attention Motor Imagery Iterative Neural Network LIF Neuron

December 8, 2023

Noise Adaptor in Spiking Neural Networks
Chen Li, Bipin Rajendran
Spiking Neural Network Low Latency Low Latency Spiking Neural Network Wind Noise Reduction

December 5, 2023

Supervised learning of spatial features with STDP and homeostasis using Spiking Neural Networks on SpiNNaker
Sergio Davies, Andrew Gait, Andrew Rowley, Alessandro Di Nuovo
Spiking Neural Network Supervised Learning Spike Train Spike Protein Spike Timing Dependent Plasticity Spatial Pattern Spatial Feature Homeostatic Design Confers

November 28, 2023

Spiking Neural Networks with Dynamic Time Steps for Vision Transformers
Gourav Datta, Zeyu Liu, Anni Li, Peter A. Beerel
Convolutional Neural Network Vision Transformer Spiking Neural Network Deep Neural Network Training Time Step

November 24, 2023

November 22, 2023

Applications of Spiking Neural Networks in Visual Place Recognition
Somayeh Hussaini, Michael Milford, Tobias Fischer
Financial Application Spiking Neural Network Place Recognition Neuromorphic Hardware Visual Place Recognition Modular Neural Network

November 20, 2023

Asynchronous Bioplausible Neuron for Spiking Neural Networks for Event-Based Vision
Sanket Kachole, Hussain Sajwani, Fariborz Baghaei Naeini, Dimitrios Makris, Yahya Zweiri
Neural Network Spiking Neural Network Spike Protein Event Based Vision Deep Equilibrium Neural Response

Spiking Neural Network

Papers

Enhancing Adaptive History Reserving by Spiking Convolutional Block Attention Module in Recurrent Neural Networks

Training a General Spiking Neural Network with Improved Efficiency and Minimum Latency

Spikformer V2: Join the High Accuracy Club on ImageNet with an SNN Ticket

Spiker+: a framework for the generation of efficient Spiking Neural Networks FPGA accelerators for inference at the edge

Shrinking Your TimeStep: Towards Low-Latency Neuromorphic Object Recognition with Spiking Neural Network

SparseProp: Efficient Event-Based Simulation and Training of Sparse Recurrent Spiking Neural Networks

Event-based Shape from Polarization with Spiking Neural Networks

Curriculum Design Helps Spiking Neural Networks to Classify Time Series

Deep Pulse-Coupled Neural Networks

Learning Long Sequences in Spiking Neural Networks

Efficient Object Detection in Autonomous Driving using Spiking Neural Networks: Performance, Energy Consumption Analysis, and Insights into Open-set Object Discovery

Astrocyte-Enabled Advancements in Spiking Neural Networks for Large Language Modeling

NiSNN-A: Non-iterative Spiking Neural Networks with Attention with Application to Motor Imagery EEG Classification

Noise Adaptor in Spiking Neural Networks

Supervised learning of spatial features with STDP and homeostasis using Spiking Neural Networks on SpiNNaker

Spiking Neural Networks with Dynamic Time Steps for Vision Transformers

RFI Detection with Spiking Neural Networks

Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Networks

Applications of Spiking Neural Networks in Visual Place Recognition

Asynchronous Bioplausible Neuron for Spiking Neural Networks for Event-Based Vision