SNN Architecture

Spiking Neural Networks (SNNs), inspired by the brain's function, aim to achieve energy-efficient machine learning by processing information as sparse spike trains. Current research focuses on developing efficient SNN architectures through automated search algorithms (like NAS) tailored to hardware constraints (e.g., memory, latency) and specific applications (e.g., image recognition, NLP). These efforts are driven by the need for low-power computation in resource-limited environments like embedded systems and IoT devices, promising significant advancements in energy-efficient artificial intelligence.

Papers

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

June 30, 2024

HASNAS: A Hardware-Aware Spiking Neural Architecture Search Framework for Neuromorphic Compute-in-Memory Systems
Rachmad Vidya Wicaksana Putra, Muhammad Shafique
Spiking Neural Network SNN Architecture

April 2, 2024

A Methodology for Improving Accuracy of Embedded Spiking Neural Networks through Kernel Size Scaling
Rachmad Vidya Wicaksana Putra, Muhammad Shafique
NCD Method Spiking Neural Network Enhancing Accuracy Accuracy Tradeoff SNN Architecture Embedded Neural Network Kernel Size

March 12, 2024

Efficient Post-Training Augmentation for Adaptive Inference in Heterogeneous and Distributed IoT Environments
Max Sponner, Lorenzo Servadei, Bernd Waschneck, Robert Wille, Akash Kumar
Neural Network Deep Learning Application Internet of Thing Environment Post Training Heterogeneous Setting Augmentation Pipeline Adaptive Inference Early Exit Neural Network SNN Architecture

February 17, 2024

SpikeNAS: A Fast Memory-Aware Neural Architecture Search Framework for Spiking Neural Network-based Autonomous Agents
Rachmad Vidya Wicaksana Putra, Muhammad Shafique
Neural Architecture Search Neural Network Architecture Spiking Neuron Spike Based SNN Architecture

January 31, 2024

SNNLP: Energy-Efficient Natural Language Processing Using Spiking Neural Networks
R. Alexander Knipper, Kaniz Mishty, Mehdi Sadi, Shubhra Kanti Karmaker Santu
Spiking Neural Network Neuromorphic Architecture Traditional Deep Learning SNN Architecture Energy Efficient Deep Learning

January 15, 2024

TT-SNN: Tensor Train Decomposition for Efficient Spiking Neural Network Training
Donghyun Lee, Ruokai Yin, Youngeun Kim, Abhishek Moitra, Yuhang Li, Priyadarshini Panda
Spiking Neural Network Tensor Decomposition Tensor Train Decomposition SNN Architecture

November 3, 2023

Enhancing Functional Data Analysis with Sequential Neural Networks: Advantages and Comparative Study
J. Zhao, J. Li, M. Chen, S. Jadhav
Comparative Study Advantage Feedback Functional Data Analysis SNN Based SNN Architecture Sequential Interaction Network

October 11, 2023

SpikePoint: An Efficient Point-based Spiking Neural Network for Event Cameras Action Recognition
Hongwei Ren, Yue Zhou, Yulong Huang, Haotian Fu, Xiaopeng Lin, Jie Song, Bojun Cheng
Spiking Neural Network Event Camera SNN Architecture Sparse Event Event Based Action Recognition Spike Driven

September 12, 2023

Epistemic Modeling Uncertainty of Rapid Neural Network Ensembles for Adaptive Learning
Atticus Beachy, Harok Bae, Jose Camberos, Ramana Grandhi
Neural Network Epistemic Uncertainty Adaptive Learning Neural Network Ensemble SNN Architecture Hypersonic Flow Aerospace Engineering

June 22, 2023

To Spike or Not to Spike? A Quantitative Comparison of SNN and CNN FPGA Implementations
Patrick Plagwitz, Frank Hannig, Jürgen Teich, Oliver Keszocze
Energy Efficient Spike Protein Empirical Comparison CNN Accelerator SNN Architecture

June 1, 2023

Auto-Spikformer: Spikformer Architecture Search
Kaiwei Che, Zhaokun Zhou, Zhengyu Ma, Wei Fang, Yanqi Chen, Shuaijie Shen, Li Yuan, Yonghong Tian
Neural Network Spiking Neural Network SNN Architecture Spikformer Architecture

March 3, 2022

Weightless Neural Networks for Efficient Edge Inference
Zachary Susskind, Aman Arora, Igor Dantas Dos Santos Miranda, Luis Armando Quintanilla Villon, Rafael Fontella Katopodis, Leandro Santiago de Araujo, Diego Leonel Cadette Dutra, Priscila Machado Vieira Lima, Felipe Maia Galvao Franca, Mauricio Breternitz, Lizy K. John
Neural Network Architecture DNN Accelerator Edge Inference SNN Architecture

January 23, 2022

Neural Architecture Search for Spiking Neural Networks
Youngeun Kim, Yuhang Li, Hyoungseob Park, Yeshwanth Venkatesha, Priyadarshini Panda
Neural Network Neural Architecture Search Spiking Neural Network SNN Architecture Neural Spike

SNN Architecture

Papers

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

HASNAS: A Hardware-Aware Spiking Neural Architecture Search Framework for Neuromorphic Compute-in-Memory Systems

A Methodology for Improving Accuracy of Embedded Spiking Neural Networks through Kernel Size Scaling

Efficient Post-Training Augmentation for Adaptive Inference in Heterogeneous and Distributed IoT Environments

SpikeNAS: A Fast Memory-Aware Neural Architecture Search Framework for Spiking Neural Network-based Autonomous Agents

SNNLP: Energy-Efficient Natural Language Processing Using Spiking Neural Networks

TT-SNN: Tensor Train Decomposition for Efficient Spiking Neural Network Training

Enhancing Functional Data Analysis with Sequential Neural Networks: Advantages and Comparative Study

SpikePoint: An Efficient Point-based Spiking Neural Network for Event Cameras Action Recognition

Epistemic Modeling Uncertainty of Rapid Neural Network Ensembles for Adaptive Learning

To Spike or Not to Spike? A Quantitative Comparison of SNN and CNN FPGA Implementations

Auto-Spikformer: Spikformer Architecture Search

Weightless Neural Networks for Efficient Edge Inference

Neural Architecture Search for Spiking Neural Networks