/SNN_benchmark

Spiking Neural Network Paper List

Framework

SNN Adversarial Robustness

  • Saima Sharmin, Nitin Rathi, Priyadarshini Panda, Kaushik Roy ECCV 2020
    " Inherent Adversarial Robustness of Deep Spiking Neural Networks: Effects of Discrete Input Encoding and Non-Linear Activations" [paper] [code]
  • Saima Sharmin, Priyadarshini Panda, Syed Shakib Sarwar, Chankyu Lee, Wachirawit Ponghiran, Kaushik Roy IJCNN 2019
    "A Comprehensive Analysis on Adversarial Robustness of Spiking Neural Networks". [paper]
  • Akhilesh Jaiswal, Amogh Agrawal, Indranil Chakraborty, Deboleena Roy, Kaushik Roy IJCNN 2019
    "On Robustness of Spin-Orbit-Torque Based Stochastic Sigmoid Neurons for Spiking Neural Networks". [paper]
  • Xueyuan She, Yun Long, Saibal Mukhopadhyay IJCNN 2019
    "Improving Robustness of ReRAM-based Spiking Neural Network Accelerator with Stochastic Spike-timing-dependent-plasticity". [paper]

Other Application

  • Allan Mancoo, Sander W. Keemink, Christian K. Machens NIPS 2020
    "Understanding spiking networks through convex optimization" [paper]
  • Seijoon Kim, Seongsik Park, Byunggook Na, Sungroh Yoon AAAI 2020
    Spiking-YOLO: "Spiking Neural Network for Energy-Efficient Object Detection" [paper]
  • Biswadeep Chakraborty, Xueyuan She
    "A Fully Spiking Hybrid Neural Network for Energy-Efficient Object Detection" [paper]

Papers

For the Spiking Neural Network studies, it can be roughly divided into three categories

  • The Conversion Method (Converting a well-trained ann to snn)
  • SNN trained with BP
  • SNN trained with Biological Plasticity Rules (STDP, Hebbian,etc)

Conversion Based Methods

  • Weihao Tan, Devdhar Patel, Robert Kozma AAAI 2021
    "Strategy and Benchmark for Converting Deep Q-Networks to Event-Driven Spiking Neural Networks" [paper]
  • Zhanglu Yan, Jun Zhou, Weng-Fai Wong AAAI 2021
    "Near Lossless Transfer Learning for Spiking Neural Networks" [paper]
  • Bing Han, Gopalakrishnan Srinivasan, and Kaushik Roy CVPR 2020
    "RMP-SNN: Residual Membrane Potential Neuron for Enabling Deeper High-Accuracy and Low-Latency Spiking Neural Network" [paper]
  • Bing Han, Kaushik Roy ECCV 2020
    "Deep Spiking Neural Network: Energy Efficiency Through Time based Coding" [paper]
  • Nitin Rathi, Gopalakrishnan Srinivasan, Priyadarshini Panda, Kaushik Roy ICLR 2020
    "Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation". [paper] [code]
  • Lei Zhang, Shengyuan Zhou, Tian Zhi, Zidong Du, Yunji Chen AAAI 2019
    TDSNN "DFrom Deep Neural Networks to Deep Spike Neural Networks with Temporal-Coding". [paper]
  • Ruizhi Chen, Hong Ma, Shaolin Xie, Peng Guo, Pin Li, Donglin Wang IJCNN 2018
    "Fast and Efficient Deep Sparse Multi-Strength Spiking Neural Networks with Dynamic Pruning".
  • Jingling Li, Weitai Hu, Ye Yuan, Hong Huo, Tao Fang ICONIP 2017
    "Bio-Inspired Deep Spiking Neural Network for Image Classification". [paper] [paper]

SNN trained with BP

  • Shibo Zhou, Xiaohua LI, Ying Chen, Sanjeev T. Chandrasekaran, Arindam Sanyal AAAI 2021
    "Temporal-Coded Deep Spiking Neural Network with Easy Training and Robust Performance" [paper] [code]
  • Hao Wu, Yueyi Zhang, ... AAAI 2021
    "Training Spiking Neural Networks with Accumulated Spiking Flow" [paper]
  • Hanle Zheng, Yujie Wu, Lei Deng, Yifan Hu, Guoqi Li AAAI 2021
    "Going Deeper With Directly-Trained Larger Spiking Neural Networks" [paper]
  • Wenrui Zhang, Peng Li NIPS 2020
    "Temporal Spike Sequence Learning via Backpropagation for Deep Spiking Neural Networks" [paper] [code]
  • Jinseok Kim, Kyungsu Kim, Jae-Joon Kim NIPS 2020
    "Unifying Activation- and Timing-based Learning Rules for Spiking Neural Networks" [paper] [code]
  • Qianyi Li, Cengiz Pehlevan NIPS 2020
    "Minimax Dynamics of Optimally Balanced Spiking Networks of Excitatory and Inhibitory Neurons" [paper]
  • Haowen Fang, Amar Shrestha, Ziyi Zhao, Qinru Qiu IJCAI 2020
    "Exploiting Neuron and Synapse Filter Dynamics in Spatial Temporal Learning of Deep Spiking Neural Network" [paper] [code]
  • Xiang Cheng, Yunzhe Hao, Jiaming Xu, Bo Xu IJCAI 2020
    LISNN: "Improving Spiking Neural Networks with Lateral Interactions for Robust Object Recognition" [paper]
  • Johannes C. Thiele, Olivier Bichler, Antoine Dupret ICLR 2020
    "SpikeGrad: An ANN-equivalent Computation Model for Implementing Backpropagation with Spikes". [paper]
  • Jordan Guerguiev, Konrad P. Körding, Blake A. Richards ICLR 2020
    "Spike-based causal inference for weight alignment". [paper] [code]
  • Kian Hamedani, Lingjia Liu, Shiya Liu, Haibo He, Yang Yi AAAI 2020
    "Deep Spiking Delayed Feedback Reservoirs and Its Application in Spectrum Sensing of MIMO-OFDM Dynamic Spectrum Sharing" [paper]
  • Wenrui Zhang, Peng Li NIPS 2019
    "Spike-Train Level Backpropagation for Training Deep Recurrent Spiking Neural Networks". [paper]
  • Yujie Wu, Lei Deng, Guoqi Li, Jun Zhu, Yuan Xie, Luping Shi AAAI 2019
    "Direct Training for Spiking Neural Networks: Faster, Larger, Better". [paper] [code]
  • Malu Zhang, Jibin Wu, Yansong Chua, Xiaoling Luo, Zihan Pan, Dan Liu, Haizhou Li AAAI 2019
    MPD-AL "An Efficient Membrane Potential Driven Aggregate-Label Learning Algorithm for Spiking Neurons". [paper]
  • Cengiz Pehlevan ICASSP 2019
    "A Spiking Neural Network with Local Learning Rules Derived from Nonnegative Similarity Matching". [paper]
  • Megumi Ito, Malte J. Rasch, Masatoshi Ishii, Atsuya Okazaki, SangBum Kim, Junka Okazawa, Akiyo Nomura, Kohji Hosokawa, Wilfried HaenschICONIP 2019
    "Training Large-Scale Spiking Neural Networks on Multi-core Neuromorphic System Using Backpropagation". [paper]
  • Johannes C. Thiele, Olivier Bichler, Antoine Dupret, Sergio Solinas, Giacomo Indiveri IJCNN 2019
    "A Spiking Network for Inference of Relations Trained with Neuromorphic Backpropagation". [paper]
  • Thomas Miconi, Jeff Clune, Kenneth O. Stanley ICML 2018
    "Differentiable plasticity: training plastic neural networks with backpropagation". [paper] [code]
  • Dongsung Huh, Terrence J. Sejnowski NIPS 2018
    "Gradient Descent for Spiking Neural Networks". [paper]
  • Yingyezhe Jin, Wenrui Zhang, Peng Li NIPS 2018
    "Hybrid Macro/Micro Level Backpropagation for Training Deep Spiking Neural Networks". [paper]

SNN trained with Biological Plasticity Rules (STDP, Hebbian,etc)

  • Chankyu Lee, Adarsh Kumar Kosta, Alex Zihao Zhu, Kenneth Chaney, Kostas Daniilidis, Kaushik Roy ECCV 2020
    "Spike-FlowNet: Event-based Optical Flow Estimation with Energy-Efficient Hybrid Neural Networks" [paper] [code]
  • Lin Zhu, Siwei Dong, Jianing Li, Tiejun Huang, Yonghong Tian CVPR 2020
    "Retina-Like Visual Image Reconstruction via Spiking Neural Model" [paper]
  • Qianhui Liu, Haibo Ruan, Dong Xing, Huajin Tang, Gang Pan AAAI 2020
    "Effective AER Object Classification Using Segmented Probability-Maximization Learning in Spiking Neural Networks" AAAI (2020 Oral). [paper]
  • Zuozhu Liu, Thiparat Chotibut, Christopher Hillar, Shaowei Lin AAAI 2020
    "Biologically Plausible Sequence Learning with Spiking Neural Networks" [paper] [code]
  • Shenglan Li, Qiang Yu AAAI 2020
    "New Efficient Multi-Spike Learning for Fast Processing and Robust Learning" [paper]
  • Pengjie Gu, Rong Xiao, Gang Pan, Huajin Tang IJCAI 2019
    STCA: "STCA: Spatio-Temporal Credit Assignment with Delayed Feedback in Deep Spiking Neural Networks". [paper] [code]
  • Rong Xiao, Qiang Yu, Rui Yan, Huajin Tang IJCAI 2019
    "Fast and Accurate Classification with a Multi-Spike Learning Algorithm for Spiking Neurons". [paper]
  • Lakshay Sahni, Debasrita Chakraborty, Ashish Ghosh AAAI 2019
    "Implementation of Boolean AND and OR Logic Gates with Biologically Reasonable Time Constants in Spiking Neural Networks". [paper]
  • Robert Luke, David McAlpine ICASSP 2019
    "A Spiking Neural Network Approach to Auditory Source Lateralisation". [paper]
  • Hui Yan, Xinle Liu, Hong Huo, Tao Fang ICONIP 2019
    "Mechanisms of Reward-Modulated STDP and Winner-Take-All in Bayesian Spiking Decision-Making Circuit". [paper]
  • Yanli Yao, Qiang Yu, Longbiao Wang, Jianwu Dang IJCNN 2019
    "A Spiking Neural Network with Distributed Keypoint Encoding for Robust Sound Recognition". [paper]
  • Pierre Falez, Pierre Tirilly, Ioan Marius Bilasco, Philippe Devienne, Pierre Boulet IJCNN 2019
    "Multi-layered Spiking Neural Network with Target Timestamp Threshold Adaptation and STDP". [paper]
  • Jibin Wu, Yansong Chua, Malu Zhang, Qu Yang, Guoqi Li, Haizhou Li IJCNN 2019
    "Deep Spiking Neural Network with Spike Count based Learning Rule". [paper]
  • Maximilian P. R. Löhr, Daniel Schmid, Heiko Neumann IJCNN 2019
    "Motion Integration and Disambiguation by Spiking V1-MT-MSTl Feedforward-Feedback Interaction". [paper]
  • Esma Mansouri-Benssassi, Juan Ye IJCNN 2019
    "Speech Emotion Recognition With Early Visual Cross-modal Enhancement Using Spiking Neural Networks". [paper]
  • Mikhail Kiselev, Andrey Lavrentyev IJCNN 2019
    "A Preprocessing Layer in Spiking Neural Networks - Structure, Parameters, Performance Criteria". [paper] *Won-Mook Kang, Chul-Heung Kim, Soochang Lee, Sung Yun Woo, Jong-Ho Bae, Byung-Gook Park, Jong-Ho Lee IJCNN 2019
    "A Spiking Neural Network with a Global Self-Controller for Unsupervised Learning Based on Spike-Timing-Dependent Plasticity Using Flash Memory Synaptic Devices". [paper]
  • Lyes Khacef, Benoît Miramond, Diego Barrientos, Andres Upegui IJCNN 2019
    "Self-organizing neurons: toward brain-inspired unsupervised learning". [paper]
  • Peter O'Connor, Efstratios Gavves, Matthias Reisser, Max Welling ICLR 2018
    "Temporally Efficient Deep Learning with Spikes". [paper]
  • Aditya Gilra, Wulfram Gerstner ICML 2018
    "Non-Linear Motor Control by Local Learning in Spiking Neural Networks". [paper] *Guillaume Bellec, Darjan Salaj, Anand Subramoney, Robert A. Legenstein, Wolfgang Maass NIPS 2018
    "Long short-term memory and Learning-to-learn in networks of spiking neurons". [paper]
  • Sumit Bam Shrestha, Garrick Orchard NIPS 2018
    SLAYER "Spike Layer Error Reassignment in Time". [paper] [code]
  • Yu Qi, Jiangrong Shen, Yueming Wang, Huajin Tang, Hang Yu, Zhaohui Wu, Gang Pan IJCAI 2018
    Jointly Learning Network Connections and Link Weights in Spiking Neural Networks". [paper]
  • Qi Xu, Yu Qi, Hang Yu, Jiangrong Shen, Huajin Tang, Gang Pan IJCAI 2018
    CSNN "An Augmented Spiking based Framework with Perceptron-Inception". [paper]
  • Tielin Zhang, Yi Zeng, Dongcheng Zhao, Bo Xu IJCAI 2018
    VPSNN Tielin Zhang, Yi Zeng, Dongcheng Zhao, Bo Xu. [paper]
  • Alireza Alemi, Christian K. Machens, Sophie Denève, Jean-Jacques E. Slotine AAAI 2018
    "Learning Nonlinear Dynamics in Efficient, Balanced Spiking Networks Using Local Plasticity Rules". [paper]
  • Tielin Zhang, Yi Zeng, Dongcheng Zhao, Mengting Shi AAAI 2018
    "A Plasticity-Centric Approach to Train the Non-Differential Spiking Neural Networks". [paper]
  • Alireza Bagheri, Osvaldo Simeone, Bipin Rajendran ICASSP 2018
    "Training Probabilistic Spiking Neural Networks with First- To-Spike Decoding". [paper]
  • Qiang Yu, Longbiao Wang, Jianwu Dang ICONIP 2018
    "Efficient Multi-spike Learning with Tempotron-Like LTP and PSD-Like LTD". [paper]
  • Jiaxing Liu, Guoping Zhao IJCNN 2018
    "A bio-inspired SOSNN model for object recognition". [paper]
  • Amirhossein Tavanaei, Zachary Kirby, Anthony S. Maida IJCNN 2018
    "Training Spiking ConvNets by STDP and Gradient Descent". [paper]
  • Yu Miao, Huajin Tang, Gang Pan IJCNN 2018
    "A Supervised Multi-Spike Learning Algorithm for Spiking Neural Networks". [paper]
  • Timoleon Moraitis, Abu Sebastian, Evangelos Eleftheriou IJCNN 2018
    "Spiking Neural Networks Enable Two-Dimensional Neurons and Unsupervised Multi-Timescale Learning". [paper]
  • Sam Slade, Li Zhang IJCNN 2018
    "Topological Evolution of Spiking Neural Networks". [paper]
  • Ruizhi Chen, Hong Ma, Peng Guo, Shaolin Xie, Pin Li, Donglin Wang IJCNN 2018
    "Low Latency Spiking ConvNets with Restricted Output Training and False Spike Inhibition". [paper]
  • Pierre Falez, Pierre Tirilly, Ioan Marius Bilasco, Philippe Devienne, Pierre Boulet IJCNN 2018
    "Mastering the Output Frequency in Spiking Neural Networks". [paper]
  • Daqi Liu, Shigang Yue IJCNN 2018
    "Video-Based Disguise Face Recognition Based on Deep Spiking Neural Network". [paper]
  • Johannes C. Thiele, Olivier Bichler, Antoine Dupret IJCNN 2018
    "A Timescale Invariant STDP-Based Spiking Deep Network for Unsupervised Online Feature Extraction from Event-Based Sensor Data". [paper]
  • Hananel Hazan, Daniel J. Saunders, Darpan T. Sanghavi, Hava T. Siegelmann, Robert Kozma IJCNN 2018
    "Unsupervised Learning with Self-Organizing Spiking Neural Networks". [paper]
  • Daniel J. Saunders, Hava T. Siegelmann, Robert Kozma, Miklós Ruszinkó IJCNN 2018
    "STDP Learning of Image Patches with Convolutional Spiking Neural Networks". [paper]
  • Jibin Wu, Yansong Chua, Haizhou Li IJCNN 2018
    "A Biologically Plausible Speech Recognition Framework Based on Spiking Neural Networks". [paper]
  • Antonio Jimeno-Yepes, Jianbin Tang, Benjamin Scott Mashford IJCAI 2017
    "Improving Classification Accuracy of Feedforward Neural Networks for Spiking Neuromorphic Chips". [paper]
  • Zhanhao Hu, Tao Wang, Xiaolin Hu ICONIP 2017
    "An STDP-Based Supervised Learning Algorithm for Spiking Neural Network". [paper]
  • Lin Zuo, Shan Chen, Hong Qu, Malu Zhang ICONIP 2017
    "A Fast Precise-Spike and Weight-Comparison Based Learning Approach for Evolving Spiking Neural Networks". [paper]
  • Amirhossein Tavanaei, Anthony S. Maida IJCNN 2017
    "Multi-layer unsupervised learning in a spiking convolutional neural network". [paper]
  • Takashi Matsubara IJCNN 2017
    "Spike timing-dependent conduction delay learning model classifying spatio-temporal spike patterns". [paper]
  • Laxmi R. Iyer, Arindam Basu IJCNN 2017
    "Unsupervised learning of event-based image recordings using spike-timing-dependent plasticity". [paper]
  • Gopalakrishnan Srinivasan, Sourjya Roy, Vijay Raghunathan, Kaushik Roy IJCNN 2017
    "Spike timing dependent plasticity based enhanced self-learning for efficient pattern recognition in spiking neural networks". [paper]
  • Amar Shrestha, Khadeer Ahmed, Yanzhi Wang, Qinru Qiu IJCNN 2017
    "Stable spike-timing dependent plasticity rule for multilayer unsupervised and supervised learning". [paper]
  • Timoleon Moraitis, Abu Sebastian, Irem Boybat, Manuel Le Gallo, Tomas Tuma, Evangelos Eleftheriou IJCNN 2017
    "Fatiguing STDP: Learning from spike-timing codes in the presence of rate codes". [paper]
  • Yingyezhe Jin, Peng Li IJCNN 2017
    "Calcium-modulated supervised spike-timing-dependent plasticity for readout training and sparsification of the liquid state machine". [paper]
  • Amirali Amirsoleimani, Majid Ahmadi, Arash Ahmadi IJCNN 2017
    "STDP-based unsupervised learning of memristive spiking neural network by Morris-Lecar model". [paper]