Spiking Neural Network Paper List

code

• BindsNet[code]
  
• Brain2[code]
  
• SpykeTorch[code]
  
• Norse[code]
  
• SpikingFlow[code]
  
• Nengo[code]
  
• PySNN[code]
  
• SNN_toolbox[code]
  

Papers

CVPR2020

• Bing Han, Gopalakrishnan Srinivasan, and Kaushik Roy "RMP-SNN: Residual Membrane Potential Neuron for Enabling Deeper High-Accuracy and Low-Latency Spiking Neural Network" [paper]
• Lin Zhu, Siwei Dong, Jianing Li, Tiejun Huang, Yonghong Tian "Retina-Like Visual Image Reconstruction via Spiking Neural Model" [paper]

ECCV2020

• Bing Han, Kaushik Roy "Deep Spiking Neural Network: Energy Efficiency Through Time based Coding" [paper]
• Chankyu Lee, Adarsh Kumar Kosta, Alex Zihao Zhu, Kenneth Chaney, Kostas Daniilidis, Kaushik Roy "Spike-FlowNet: Event-based Optical Flow Estimation with Energy-Efficient Hybrid Neural Networks" [paper]
• Saima Sharmin, Nitin Rathi, Priyadarshini Panda, Kaushik Roy " Inherent Adversarial Robustness of Deep Spiking Neural Networks: Effects of Discrete Input Encoding and Non-Linear Activations" [paper]

IJCAI2020

• Haowen Fang, Amar Shrestha, Ziyi Zhao, Qinru Qiu
  "Exploiting Neuron and Synapse Filter Dynamics in Spatial Temporal Learning of Deep Spiking Neural Network" [paper] [code]
• Haowen Fang, Amar Shrestha, Ziyi Zhao, Qinru Qiu
  LISNN: "Improving Spiking Neural Networks with Lateral Interactions for Robust Object Recognition" [paper] [code]

ICLR2020

• Johannes C. Thiele, Olivier Bichler, Antoine Dupret
  "SpikeGrad: An ANN-equivalent Computation Model for Implementing Backpropagation with Spikes". [paper]
• Jordan Guerguiev, Konrad P. Körding, Blake A. Richards
  "Spike-based causal inference for weight alignment". [paper] [code]
• Nitin Rathi, Gopalakrishnan Srinivasan, Priyadarshini Panda, Kaushik Roy
  "Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation". [paper] [code]

AAAI2020

• Qianhui Liu, Haibo Ruan, Dong Xing, Huajin Tang, Gang Pan
  "Effective AER Object Classification Using Segmented Probability-Maximization Learning in Spiking Neural Networks" AAAI (2020 Oral). [paper]
• Seijoon Kim, Seongsik Park, Byunggook Na, Sungroh Yoon
  Spiking-YOLO: "Spiking Neural Network for Energy-Efficient Object Detection" [paper]
• Zuozhu Liu, Thiparat Chotibut, Christopher Hillar, Shaowei Lin
  "Biologically Plausible Sequence Learning with Spiking Neural Networks" [paper] [code]
• Kian Hamedani, Lingjia Liu, Shiya Liu, Haibo He, Yang Yi
  "Deep Spiking Delayed Feedback Reservoirs and Its Application in Spectrum Sensing of MIMO-OFDM Dynamic Spectrum Sharing" [paper]

NIPS2019

• Wenrui Zhang, Peng Li
  "Spike-Train Level Backpropagation for Training Deep Recurrent Spiking Neural Networks". [paper]
• Mohammad Reza Keshtkaran, Chethan Pandarinath
  "Enabling hyperparameter optimization in sequential autoencoders for spiking neural data". [paper]

IJCAI2019

• Pengjie Gu, Rong Xiao, Gang Pan, Huajin Tang
  STCA: "STCA: Spatio-Temporal Credit Assignment with Delayed Feedback in Deep Spiking Neural Networks". [paper] [code]

• Rong Xiao, Qiang Yu, Rui Yan, Huajin Tang
  "Fast and Accurate Classification with a Multi-Spike Learning Algorithm for Spiking Neurons". [paper]

AAAI2019

• Yujie Wu, Lei Deng, Guoqi Li, Jun Zhu, Yuan Xie, Luping Shi
  "Direct Training for Spiking Neural Networks: Faster, Larger, Better". [paper] [code]
• Yujie Wu, Lei Deng, Guoqi Li, Jun Zhu, Yuan Xie, Luping Shi
  TDSNN "Direct Training for Spiking Neural Networks: Faster, Larger, Better". [paper]
• Malu Zhang, Jibin Wu, Yansong Chua, Xiaoling Luo, Zihan Pan, Dan Liu, Haizhou Li
  MPD-AL "An Efficient Membrane Potential Driven Aggregate-Label Learning Algorithm for Spiking Neurons". [paper]
• Lakshay Sahni, Debasrita Chakraborty, Ashish Ghosh
  "Implementation of Boolean AND and OR Logic Gates with Biologically Reasonable Time Constants in Spiking Neural Networks". [paper]

ICASSP2019

• Cengiz Pehlevan
  "A Spiking Neural Network with Local Learning Rules Derived from Nonnegative Similarity Matching". [paper]
• Robert Luke, David McAlpine
  "A Spiking Neural Network Approach to Auditory Source Lateralisation". [paper]

ICONIP2019

• Hui Yan, Xinle Liu, Hong Huo, Tao Fang
  "Mechanisms of Reward-Modulated STDP and Winner-Take-All in Bayesian Spiking Decision-Making Circuit". [paper]
• Megumi Ito, Malte J. Rasch, Masatoshi Ishii, Atsuya Okazaki, SangBum Kim, Junka Okazawa, Akiyo Nomura, Kohji Hosokawa, Wilfried Haensch
  "Training Large-Scale Spiking Neural Networks on Multi-core Neuromorphic System Using Backpropagation". [paper]
• Dhvani Shah, Grace Y. Wang, Maryam Gholami Doborjeh, Zohreh Gholami Doborjeh, Nikola Kasabov
  "Deep Learning of EEG Data in the NeuCube Brain-Inspired Spiking Neural Network Architecture for a Better Understanding of Depression". [paper]

IJCNN2019

• Yanli Yao, Qiang Yu, Longbiao Wang, Jianwu Dang
  "A Spiking Neural Network with Distributed Keypoint Encoding for Robust Sound Recognition". [paper]
• Catherine D. Schuman, James S. Plank, Grant Bruer, Jeremy Anantharaj
  "Non-Traditional Input Encoding Schemes for Spiking Neuromorphic Systems". [paper]
• Maximilian P. R. Löhr, Daniel Schmid, Heiko Neumann
  "Motion Integration and Disambiguation by Spiking V1-MT-MSTl Feedforward-Feedback Interaction". [paper]
• Pierre Falez, Pierre Tirilly, Ioan Marius Bilasco, Philippe Devienne, Pierre Boulet
  "Multi-layered Spiking Neural Network with Target Timestamp Threshold Adaptation and STDP". [paper]
• Kyunghee Lee, Hongchi Shi
  "A Modular Approach to Construction of Spiking Neural Networks". [paper]
• Johannes C. Thiele, Olivier Bichler, Antoine Dupret, Sergio Solinas, Giacomo Indiveri
  "A Spiking Network for Inference of Relations Trained with Neuromorphic Backpropagation". [paper]
• Esma Mansouri-Benssassi, Juan Ye
  "Speech Emotion Recognition With Early Visual Cross-modal Enhancement Using Spiking Neural Networks". [paper]
• Xueyuan She, Yun Long, Saibal Mukhopadhyay
  "Improving Robustness of ReRAM-based Spiking Neural Network Accelerator with Stochastic Spike-timing-dependent-plasticity". [paper]
• Jibin Wu, Yansong Chua, Malu Zhang, Qu Yang, Guoqi Li, Haizhou Li
  "Deep Spiking Neural Network with Spike Count based Learning Rule". [paper]
• Mikhail Kiselev, Andrey Lavrentyev
  "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
  "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
  "Self-organizing neurons: toward brain-inspired unsupervised learning". [paper]
• Saima Sharmin, Priyadarshini Panda, Syed Shakib Sarwar, Chankyu Lee, Wachirawit Ponghiran, Kaushik Roy
  "A Comprehensive Analysis on Adversarial Robustness of Spiking Neural Networks". [paper]
• Akhilesh Jaiswal, Amogh Agrawal, Indranil Chakraborty, Deboleena Roy, Kaushik Roy
  "On Robustness of Spin-Orbit-Torque Based Stochastic Sigmoid Neurons for Spiking Neural Networks". [paper]

ICLR2018

• Peter O'Connor, Efstratios Gavves, Matthias Reisser, Max Welling
  "Temporally Efficient Deep Learning with Spikes". [paper]

ICML2018

• Aditya Gilra, Wulfram Gerstner
  "Non-Linear Motor Control by Local Learning in Spiking Neural Networks". [paper]
• Thomas Miconi, Jeff Clune, Kenneth O. Stanley
  "Differentiable plasticity: training plastic neural networks with backpropagation". [paper] [code]

NIPS2018

• Guillaume Bellec, Darjan Salaj, Anand Subramoney, Robert A. Legenstein, Wolfgang Maass
  "Long short-term memory and Learning-to-learn in networks of spiking neurons". [paper]
• Sumit Bam Shrestha, Garrick Orchard
  SLAYER "Spike Layer Error Reassignment in Time". [paper] [code]
• Dongsung Huh, Terrence J. Sejnowski
  "Gradient Descent for Spiking Neural Networks". [paper]
• Yingyezhe Jin, Wenrui Zhang, Peng Li
  "Hybrid Macro/Micro Level Backpropagation for Training Deep Spiking Neural Networks". [paper]
• Lea Duncker, Maneesh Sahani
  "Temporal alignment and latent Gaussian process factor inference in population spike trains". [paper]

IJCAI2018

• Yu Qi, Jiangrong Shen, Yueming Wang, Huajin Tang, Hang Yu, Zhaohui Wu, Gang Pan
  Jointly Learning Network Connections and Link Weights in Spiking Neural Networks". [paper]
• Qi Xu, Yu Qi, Hang Yu, Jiangrong Shen, Huajin Tang, Gang Pan
  CSNN "An Augmented Spiking based Framework with Perceptron-Inception". [paper]
• Tielin Zhang, Yi Zeng, Dongcheng Zhao, Bo Xu
  VPSNN Tielin Zhang, Yi Zeng, Dongcheng Zhao, Bo Xu. [paper]

AAAI2018

• Alireza Alemi, Christian K. Machens, Sophie Denève, Jean-Jacques E. Slotine
  "Learning Nonlinear Dynamics in Efficient, Balanced Spiking Networks Using Local Plasticity Rules". [paper]
• Tielin Zhang, Yi Zeng, Dongcheng Zhao, Mengting Shi
  "A Plasticity-Centric Approach to Train the Non-Differential Spiking Neural Networks". [paper]

ICASSP2018

• Alireza Bagheri, Osvaldo Simeone, Bipin Rajendran
  "Training Probabilistic Spiking Neural Networks with First- To-Spike Decoding". [paper]
• Robert Luke, David McAlpine
  "A Spiking Neural Network Approach to Auditory Source Lateralisation". [paper]

ICONIP2018

• Sou Nobukawa, Haruhiko Nishimura, Teruya Yamanishi
  "Skewed and Long-Tailed Distributions of Spiking Activity in Coupled Network Modules with Log-Normal Synaptic Weight Distribution". [paper]
• Qiang Yu, Longbiao Wang, Jianwu Dang
  "Efficient Multi-spike Learning with Tempotron-Like LTP and PSD-Like LTD". [paper]
• Hiroaki Uchida, Toshimichi Saito
  "A Ladder-Type Digital Spiking Neural Network". [paper]
• Durgesh Nandini, Elisa Capecci, Lucien Koefoed, Ibai Laña, Gautam Kishore Shahi, Nikola Kasabov
  "Modelling and Analysis of Temporal Gene Expression Data Using Spiking Neural Networks". [paper]
• Dong Niu, Dengju Li, Rui Yan, Huajin Tang
  "A Gesture Recognition Method Based on Spiking Neural Networks for Cognition Development". [paper]
• Jack Dray, Elisa Capecci, Nikola Kasabov
  "Spiking Neural Networks for Cancer Gene Expression Time Series Modelling and Analysis". [paper]

IJCNN2018

• Jiaxing Liu, Guoping Zhao
  "A bio-inspired SOSNN model for object recognition". [paper]
• Amirhossein Tavanaei, Zachary Kirby, Anthony S. Maida
  "Training Spiking ConvNets by STDP and Gradient Descent". [paper]
• Renato C. Duarte, Marvin Uhlmann, Dick den van Broek, Hartmut Fitz, Karl Magnus Petersson, Abigail Morrison
  "Encoding symbolic sequences with spiking neural reservoirs". [paper]
• Barna Zajzon, Renato C. Duarte, Abigail Morrison
  "Transferring State Representations in Hierarchical Spiking Neural Networks". [paper]
• Catherine D. Schuman, Grant Bruer, Aaron R. Young, Mark E. Dean, James S. Plank
  "Understanding Selection And Diversity For Evolution Of Spiking Recurrent Neural Networks". [paper]
• Yu Miao, Huajin Tang, Gang Pan
  "A Supervised Multi-Spike Learning Algorithm for Spiking Neural Networks". [paper]
• Timoleon Moraitis, Abu Sebastian, Evangelos Eleftheriou
  "Spiking Neural Networks Enable Two-Dimensional Neurons and Unsupervised Multi-Timescale Learning". [paper]
• Ruizhi Chen, Hong Ma, Shaolin Xie, Peng Guo, Pin Li, Donglin Wang
  "Fast and Efficient Deep Sparse Multi-Strength Spiking Neural Networks with Dynamic Pruning". [paper]
• Sam Slade, Li Zhang
  "Topological Evolution of Spiking Neural Networks". [paper]
• Juan Pedro Dominguez-Morales, Qian Liu, Robert James, Daniel Gutierrez-Galan, Angel Jiménez-Fernandez, Simon Davidson, Steve B. Furber
  "Deep Spiking Neural Network model for time-variant signals classification: a real-time speech recognition approach". [paper]
• Ruizhi Chen, Hong Ma, Peng Guo, Shaolin Xie, Pin Li, Donglin Wang
  "Low Latency Spiking ConvNets with Restricted Output Training and False Spike Inhibition". [paper]
• Pierre Falez, Pierre Tirilly, Ioan Marius Bilasco, Philippe Devienne, Pierre Boulet
  "Mastering the Output Frequency in Spiking Neural Networks". [paper]
• Daqi Liu, Shigang Yue
  "Video-Based Disguise Face Recognition Based on Deep Spiking Neural Network". [paper]
• Hoyoung Tang, Heetak Kim, Donghyeon Cho, Jongsun Park
  "Spike Counts Based Low Complexity Learning with Binary Synapse". [paper]
• Jibin Wu, Yansong Chua, Haizhou Li
  "A Biologically Plausible Speech Recognition Framework Based on Spiking Neural Networks". [paper]
• William Severa, Rich Lehoucq, Ojas Parekh, James B. Aimone
  "Spiking Neural Algorithms for Markov Process Random Walk". [paper]
• Johannes C. Thiele, Olivier Bichler, Antoine Dupret
  "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
  "Unsupervised Learning with Self-Organizing Spiking Neural Networks". [paper]
• Daniel J. Saunders, Hava T. Siegelmann, Robert Kozma, Miklós Ruszinkó
  "STDP Learning of Image Patches with Convolutional Spiking Neural Networks". [paper]

IJCAI2017

• Antonio Jimeno-Yepes, Jianbin Tang, Benjamin Scott Mashford
  "Improving Classification Accuracy of Feedforward Neural Networks for Spiking Neuromorphic Chips". [paper]

ICONIP2017

• Zhanhao Hu, Tao Wang, Xiaolin Hu
  "An STDP-Based Supervised Learning Algorithm for Spiking Neural Network". [paper]
• Jingling Li, Weitai Hu, Ye Yuan, Hong Huo, Tao Fang
  "Bio-Inspired Deep Spiking Neural Network for Image Classification". [paper]
• Lin Zuo, Shan Chen, Hong Qu, Malu Zhang
  "A Fast Precise-Spike and Weight-Comparison Based Learning Approach for Evolving Spiking Neural Networks". [paper]
• Junxiu Liu, Xingyue Huang, Yuling Luo, Yi Cao
  "An Energy-Aware Hybrid Particle Swarm Optimization Algorithm for Spiking Neural Network Mapping". [paper]
• Lin Zuo, Linyao Ma, Yanqing Xiao, Malu Zhang, Hong Qu
  "A Dynamic Region Generation Algorithm for Image Segmentation Based on Spiking Neural Network". [paper]

IJCNN2017

• Timoleon Moraitis, Abu Sebastian, Irem Boybat, Manuel Le Gallo, Tomas Tuma, Evangelos Eleftheriou
  "Fatiguing STDP: Learning from spike-timing codes in the presence of rate codes". [paper]
• Takashi Matsubara
  "Spike timing-dependent conduction delay learning model classifying spatio-temporal spike patterns". [paper]
• Laxmi R. Iyer, Arindam Basu
  "Unsupervised learning of event-based image recordings using spike-timing-dependent plasticity". [paper]
• Gopalakrishnan Srinivasan, Sourjya Roy, Vijay Raghunathan, Kaushik Roy
  "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
  "Stable spike-timing dependent plasticity rule for multilayer unsupervised and supervised learning". [paper]
• Yingyezhe Jin, Peng Li
  "Calcium-modulated supervised spike-timing-dependent plasticity for readout training and sparsification of the liquid state machine". [paper]
• Stephen J. Verzi, Craig M. Vineyard, Eric D. Vugrin, Meghan A. Galiardi, Conrad D. James, James B. Aimone
  "Optimization-based computation with spiking neurons". [paper]
• Amirhossein Tavanaei, Anthony S. Maida
  "Multi-layer unsupervised learning in a spiking convolutional neural network". [paper]
• Tae Seung Kang, Arunava Banerjee
  "Learning deterministic spiking neuron feedback controllers". [paper]
• Amirali Amirsoleimani, Majid Ahmadi, Arash Ahmadi
  "STDP-based unsupervised learning of memristive spiking neural network by Morris-Lecar model". [paper]