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

November 11, 2024

Randomized Forward Mode Gradient for Spiking Neural Networks in Scientific Machine Learning
Ruyin Wan, Qian Zhang, George Em Karniadakis
Neural Network Spiking Neural Network Back Propagation Neuromorphic Hardware Scientific Machine Learning Spike Based

November 10, 2024

Are Neuromorphic Architectures Inherently Privacy-preserving? An Exploratory Study
Ayana Moshruba, Ihsen Alouani, Maryam Parsa
Spiking Neural Network Exploratory Study Private Stochastic Gradient Descent Neuromorphic Architecture User Configurable Privacy Defense

November 7, 2024

Zero-Shot Temporal Resolution Domain Adaptation for Spiking Neural Networks
Sanja Karilanova, Maxime Fabre, Emre Neftci, Ayça Özçelikkale
Zero Shot Spiking Neural Network Network Programming Neuromorphic Hardware Temporal Resolution Spiking Neuron Neuronal Dynamic

November 5, 2024

November 3, 2024

Energy-Aware FPGA Implementation of Spiking Neural Network with LIF Neurons
Asmer Hamid Ali, Mozhgan Navardi, Tinoosh Mohsenin
Spiking Neural Network Single Neuron Level TinyML Model Tiny Machine Learning SNN Model FPGA Implementation Leaky Integrate and Fire

November 1, 2024

Differentiable architecture search with multi-dimensional attention for spiking neural networks
Yilei Man, Linhai Xie, Shushan Qiao, Yumei Zhou, Delong Shang
Neural Network Neural Architecture Search Spiking Neural Network Differentiable Architecture Search Dimensional Attention SNN Based

October 31, 2024

October 24, 2024

Spatial-Temporal Search for Spiking Neural Networks
Kaiwei Che, Zhaokun Zhou, Li Yuan, Jianguo Zhang, Yonghong Tian, Luziwei Leng
Neural Network Spiking Neural Network Neural Topic Biological Neural Network

October 22, 2024

Neuronal Competition Groups with Supervised STDP for Spike-Based Classification
Gaspard Goupy, Pierre Tirilly, Ioan Marius Bilasco
Classification Code Spiking Neural Network Neuromorphic Hardware Spike Timing Dependent Plasticity Spike Encoding

October 21, 2024

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

October 12, 2024

EG-SpikeFormer: Eye-Gaze Guided Transformer on Spiking Neural Networks for Medical Image Analysis
Yi Pan, Hanqi Jiang, Junhao Chen, Yiwei Li, Huaqin Zhao, Yifan Zhou, Peng Shu, Zihao Wu, Zhengliang Liu, Dajiang Zhu, Xiang Li, Yohannes Abate, Tianming Liu
Transformer Based Spiking Neural Network Medical Image Analysis Neuromorphic Computing Neuromorphic Hardware SNN Architecture

October 11, 2024

Energy-efficient SNN Architecture using 3nm FinFET Multiport SRAM-based CIM with Online Learning
Lucas Huijbregts, Liu Hsiao-Hsuan, Paul Detterer, Said Hamdioui, Amirreza Yousefzadeh, Rajendra Bishnoi
Spiking Neural Network Online Learning Energy Efficient Complementary Metal Oxide Semiconductor Current Artificial Intelligence

October 10, 2024

October 7, 2024

Hardware-Software Co-optimised Fast and Accurate Deep Reconfigurable Spiking Inference Accelerator Architecture Design Methodology
Anagha Nimbekar, Prabodh Katti, Chen Li, Bashir M. Al-Hashimi, Amit Acharyya, Bipin Rajendran
Spiking Neural Network Hardware Accelerator Complementary Metal Oxide Semiconductor SoC FPGA

October 4, 2024

PRF: Parallel Resonate and Fire Neuron for Long Sequence Learning in Spiking Neural Networks
Yulong Huang, Zunchang Liu, Changchun Feng, Xiaopeng Lin, Hongwei Ren, Haotian Fu, Yue Zhou, Hong Xing, Bojun Cheng
Spiking Neural Network Long Sequence

Spiking Neural Network

Papers

Randomized Forward Mode Gradient for Spiking Neural Networks in Scientific Machine Learning

Are Neuromorphic Architectures Inherently Privacy-preserving? An Exploratory Study

Zero-Shot Temporal Resolution Domain Adaptation for Spiking Neural Networks

Flashy Backdoor: Real-world Environment Backdoor Attack on SNNs with DVS Cameras

SpiDR: A Reconfigurable Digital Compute-in-Memory Spiking Neural Network Accelerator for Event-based Perception

Energy-Aware FPGA Implementation of Spiking Neural Network with LIF Neurons

Differentiable architecture search with multi-dimensional attention for spiking neural networks

Approaches to human activity recognition via passive radar

ETTFS: An Efficient Training Framework for Time-to-First-Spike Neuron

Spatial-Temporal Search for Spiking Neural Networks

Neuronal Competition Groups with Supervised STDP for Spike-Based Classification

Spiking Neural Networks as a Controller for Emergent Swarm Agents

Enhancing SNN-based Spatio-Temporal Learning: A Benchmark Dataset and Cross-Modality Attention Model

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

EG-SpikeFormer: Eye-Gaze Guided Transformer on Spiking Neural Networks for Medical Image Analysis

Energy-efficient SNN Architecture using 3nm FinFET Multiport SRAM-based CIM with Online Learning

SNN-PAR: Energy Efficient Pedestrian Attribute Recognition via Spiking Neural Networks

Comprehensive Online Training and Deployment for Spiking Neural Networks

Hardware-Software Co-optimised Fast and Accurate Deep Reconfigurable Spiking Inference Accelerator Architecture Design Methodology

PRF: Parallel Resonate and Fire Neuron for Long Sequence Learning in Spiking Neural Networks