Binary Spike

Binary spike neural networks (SNNs) leverage the brain's energy-efficient, event-driven communication style by representing information as binary spikes, aiming to improve the performance and energy efficiency of artificial neural networks. Current research focuses on enhancing SNN performance in complex tasks like object detection and zero-shot learning through architectural innovations (e.g., SpikeYOLO, Spiking Tucker Fusion Transformer) and improved training methods (e.g., multi-bit mechanisms, dynamic timestep adjustments, and joint ANN-SNN training). These advancements are significant because they address limitations in SNNs' representational capacity and training efficiency, paving the way for their wider adoption in energy-constrained applications and neuromorphic hardware.

Papers

July 30, 2024

Integer-Valued Training and Spike-Driven Inference Spiking Neural Network for High-performance and Energy-efficient Object Detection
Xinhao Luo, Man Yao, Yuhong Chou, Bo Xu, Guoqi Li
Training Data Object Detection State of the Art Neuromorphic Datasets High Performance Neuromorphic Event Binary Spike

July 11, 2024

Spiking Tucker Fusion Transformer for Audio-Visual Zero-Shot Learning
Wenrui Li, Penghong Wang, Ruiqin Xiong, Xiaopeng Fan
Audio Visual Temporal Fusion Spiking Transformer Binary Spike

July 8, 2024

Multi-Bit Mechanism: A Novel Information Transmission Paradigm for Spiking Neural Networks
Yongjun Xiao, Xianlong Tian, Yongqi Ding, Pei He, Mengmeng Jing, Lin Zuo
Spiking Neural Network P Bit Transmission Data Binary Spike Communication Model

March 11, 2024

SiGNN: A Spike-induced Graph Neural Network for Dynamic Graph Representation Learning
Dong Chen, Shuai Zheng, Muhao Xu, Zhenfeng Zhu, Yao Zhao
Multi Scale Spatiotemporal Representation Dynamic Graph Representation Learning Binary Spike Spiking Graph Convolutional Network

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

December 4, 2023

Fully Spiking Denoising Diffusion Implicit Models
Ryo Watanabe, Yusuke Mukuta, Tatsuya Harada
Generative Model Neuromorphic Hardware Binary Spike Spiking Diffusion

September 27, 2023

Low Latency of object detection for spikng neural network
Nemin Qiu, Chuang Zhu
Neural Network Spiking Neural Network Low Latency Spike Train Binary Spike Neural Spike

August 30, 2023

A Deep Dive into the Design Space of a Dynamically Reconfigurable Cryogenic Spiking Neuron
Md Mazharul Islam, Shamiul Alam, Catherine D Schuman, Md Shafayat Hossain, Ahmedullah Aziz
Memristive Device Design Space Neural Circuit Deep Dive Binary Spike

July 10, 2023

InfLoR-SNN: Reducing Information Loss for Spiking Neural Networks
Yufei Guo, Yuanpei Chen, Liwen Zhang, Xiaode Liu, Xinyi Tong, Yuanyuan Ou, Xuhui Huang, Zhe Ma
Neural Network Spiking Neural Network Binary Spike Information Loss Membrane Potential Based Reset

June 14, 2023

High-performance deep spiking neural networks with 0.3 spikes per neuron
Ana Stanojevic, Stanisław Woźniak, Guillaume Bellec, Giovanni Cherubini, Angeliki Pantazi, Wulfram Gerstner
Neural Network Spiking Neural Network Single Neuron Level Spike Protein High Performance Binary Spike Spike Timing

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

May 27, 2023

Input-Aware Dynamic Timestep Spiking Neural Networks for Efficient In-Memory Computing
Yuhang Li, Abhishek Moitra, Tamar Geller, Priyadarshini Panda
Neural Network Spiking Neural Network Memory Computing Single Neural Network Binary Spike Static Deep Neural Network

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 2, 2023

SEENN: Towards Temporal Spiking Early-Exit Neural Networks
Yuhang Li, Tamar Geller, Youngeun Kim, Priyadarshini Panda
Spiking Neural Network Binary Spike SNN Conversion Early Exit Neural Network

January 27, 2023

Training Full Spike Neural Networks via Auxiliary Accumulation Pathway
Guangyao Chen, Peixi Peng, Guoqi Li, Yonghong Tian
Neuromorphic Hardware Auxiliary Learning Binary Spike

November 17, 2022

SMS: Spiking Marching Scheme for Efficient Long Time Integration of Differential Equations
Qian Zhang, Adar Kahana, George Em Karniadakis, Panos Stinis
Spiking Neural Network Differential Equation Binary Spike Spike Encoding Text Transmission Long Time Integration

October 6, 2022

Spiking neural networks for nonlinear regression
Alexander Henkes, Jason K. Eshraghian, Henning Wessels
Neural Network Neural Architecture Neuromorphic Hardware Second Order Binary Spike Nonlinear Regression

June 8, 2022

Solving the Spike Feature Information Vanishing Problem in Spiking Deep Q Network with Potential Based Normalization
Yinqian Sun, Yi Zeng, Yang Li
Reinforcement Learning Deep Q Network Binary Spike

May 2, 2022

Sparse Compressed Spiking Neural Network Accelerator for Object Detection
Hong-Han Lien, Tian-Sheuan Chang
Spiking Neural Network Low Power Sparse Activation Binary Spike Neural Network Accelerator

March 26, 2022

A Spiking Neural Network based on Neural Manifold for Augmenting Intracortical Brain-Computer Interface Data
Shengjie Zheng, Wenyi Li, Lang Qian, Chenggang He, Xiaojian Li
Spiking Neural Network Brain Inspired Binary Spike Neural Signal Information Processing

Binary Spike

Papers

Integer-Valued Training and Spike-Driven Inference Spiking Neural Network for High-performance and Energy-efficient Object Detection

Spiking Tucker Fusion Transformer for Audio-Visual Zero-Shot Learning

Multi-Bit Mechanism: A Novel Information Transmission Paradigm for Spiking Neural Networks

SiGNN: A Spike-induced Graph Neural Network for Dynamic Graph Representation Learning

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

Fully Spiking Denoising Diffusion Implicit Models

Low Latency of object detection for spikng neural network

A Deep Dive into the Design Space of a Dynamically Reconfigurable Cryogenic Spiking Neuron

InfLoR-SNN: Reducing Information Loss for Spiking Neural Networks

High-performance deep spiking neural networks with 0.3 spikes per neuron

Direct Learning-Based Deep Spiking Neural Networks: A Review

Input-Aware Dynamic Timestep Spiking Neural Networks for Efficient In-Memory Computing

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

SEENN: Towards Temporal Spiking Early-Exit Neural Networks

Training Full Spike Neural Networks via Auxiliary Accumulation Pathway

SMS: Spiking Marching Scheme for Efficient Long Time Integration of Differential Equations

Spiking neural networks for nonlinear regression

Solving the Spike Feature Information Vanishing Problem in Spiking Deep Q Network with Potential Based Normalization

Sparse Compressed Spiking Neural Network Accelerator for Object Detection

A Spiking Neural Network based on Neural Manifold for Augmenting Intracortical Brain-Computer Interface Data