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

August 23, 2023

Layer-wise Feedback Propagation
Leander Weber, Jim Berend, Alexander Binder, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin
Transfer Learning Spiking Neural Network Layer Wise Relevance Propagation Feedback Network Neural Predictor

August 20, 2023

Spiking-Diffusion: Vector Quantized Discrete Diffusion Model with Spiking Neural Networks
Mingxuan Liu, Jie Gan, Rui Wen, Tao Li, Yongli Chen, Hong Chen
Diffusion Model Spiking Neural Network Spike Train Diffusion Decoder Energy Efficient Neuromorphic Spiking Diffusion

August 13, 2023

RMP-Loss: Regularizing Membrane Potential Distribution for Spiking Neural Networks
Yufei Guo, Xiaode Liu, Yuanpei Chen, Liwen Zhang, Weihang Peng, Yuhan Zhang, Xuhui Huang, Zhe Ma
Neural Network Spiking Neural Network Full Potential Quantization Error Quantization Step Soft Membrane Membrane Potential

August 12, 2023

Gated Attention Coding for Training High-performance and Efficient Spiking Neural Networks
Xuerui Qiu, Rui-Jie Zhu, Yuhong Chou, Zhaorui Wang, Liang-jian Deng, Guoqi Li
Spiking Neural Network Neuromorphic Hardware Gated Attention Spike Driven Spike Representation

August 10, 2023

A Homomorphic Encryption Framework for Privacy-Preserving Spiking Neural Networks
Farzad Nikfam, Raffaele Casaburi, Alberto Marchisio, Maurizio Martina, Muhammad Shafique
Deep Neural Network Spiking Neural Network Homomorphic Encryption

August 9, 2023

Enhancing Efficient Continual Learning with Dynamic Structure Development of Spiking Neural Networks
Bing Han, Feifei Zhao, Yi Zeng, Wenxuan Pan, Guobin Shen
Spiking Neural Network Continual Learning Structural Dynamic COntinual Learning Framework Efficient Continual Learning Adaptive Continual Learning

August 8, 2023

SSTFormer: Bridging Spiking Neural Network and Memory Support Transformer for Frame-Event based Recognition
Xiao Wang, Zongzhen Wu, Yao Rong, Lin Zhu, Bo Jiang, Jin Tang, Yonghong Tian
Spiking Neural Network Recognition Rate Pattern Recognition Event Based Event Classification Memory Transformer RGB Event

August 4, 2023

Paired Competing Neurons Improving STDP Supervised Local Learning In Spiking Neural Networks
Gaspard Goupy, Pierre Tirilly, Ioan Marius Bilasco
Spiking Neural Network Neuromorphic Hardware Spike Timing Dependent Plasticity Energy Efficient Neuromorphic

August 1, 2023

Evaluating Spiking Neural Network On Neuromorphic Platform For Human Activity Recognition
Sizhen Bian, Michele Magno
Spiking Neural Network Activity Recognition Neuromorphic Processor Neuromorphic Platform

July 30, 2023

July 20, 2023

On-Sensor Data Filtering using Neuromorphic Computing for High Energy Physics Experiments
Shruti R. Kulkarni, Aaron Young, Prasanna Date, Narasinga Rao Miniskar, Jeffrey S. Vetter, Farah Fahim, Benjamin Parpillon, Jennet Dickinson, Nhan Tran, Jieun Yoo, Corrinne Mills, Morris Swartz, Petar Maksimovic, Catherine D. Schuman, Alice Bean
Spiking Neural Network Neuromorphic Computing Sensor Data High Energy Physic Sensor System Neuromorphic Model

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

July 8, 2023

A Survey of Spiking Neural Network Accelerator on FPGA
Murat Isik
Timely Survey Spiking Neural Network State of the Art Field Programmable Gate Array

July 6, 2023

A Neuromorphic Architecture for Reinforcement Learning from Real-Valued Observations
Sergio F. Chevtchenko, Yeshwanth Bethi, Teresa B. Ludermir, Saeed Afshar
Reinforcement Learning Spiking Neural Network Proximal Policy Optimization Actor Critic Algorithm Efficient Reinforcement Learning Real Data Neuromorphic Architecture

July 4, 2023

Spike-driven Transformer
Man Yao, Jiakui Hu, Zhaokun Zhou, Li Yuan, Yonghong Tian, Bo Xu, Guoqi Li
Self Attention Spiking Neural Network Spiking Transformer Spike Driven

June 30, 2023

Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings
Ilyass Hammouamri, Ismail Khalfaoui-Hassani, Timothée Masquelier
Neural Network Spiking Neural Network Dilated Convolution Spike Camera

Spiking Neural Network

Papers

Layer-wise Feedback Propagation

Spiking-Diffusion: Vector Quantized Discrete Diffusion Model with Spiking Neural Networks

Inherent Redundancy in Spiking Neural Networks

HyperSNN: A new efficient and robust deep learning model for resource constrained control applications

Expressivity of Spiking Neural Networks

RMP-Loss: Regularizing Membrane Potential Distribution for Spiking Neural Networks

Gated Attention Coding for Training High-performance and Efficient Spiking Neural Networks

A Homomorphic Encryption Framework for Privacy-Preserving Spiking Neural Networks

Enhancing Efficient Continual Learning with Dynamic Structure Development of Spiking Neural Networks

SSTFormer: Bridging Spiking Neural Network and Memory Support Transformer for Frame-Event based Recognition

Paired Competing Neurons Improving STDP Supervised Local Learning In Spiking Neural Networks

Evaluating Spiking Neural Network On Neuromorphic Platform For Human Activity Recognition

Synaptic Plasticity Models and Bio-Inspired Unsupervised Deep Learning: A Survey

Spiking Neural Networks and Bio-Inspired Supervised Deep Learning: A Survey

On-Sensor Data Filtering using Neuromorphic Computing for High Energy Physics Experiments

InfLoR-SNN: Reducing Information Loss for Spiking Neural Networks

A Survey of Spiking Neural Network Accelerator on FPGA

A Neuromorphic Architecture for Reinforcement Learning from Real-Valued Observations

Spike-driven Transformer

Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings