- BindsNet[code]
- Brain2[code]
- SpykeTorch[code]
- Norse[code]
- SpikingFlow[code]
- Nengo[code]
- PySNN[code]
- SNN_toolbox[code]
- 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]
- 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]
- 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]
- 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]
- 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]
- 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]
-
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]
- 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]
- 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]
- 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]
- 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]
- Peter O'Connor, Efstratios Gavves, Matthias Reisser, Max Welling
"Temporally Efficient Deep Learning with Spikes". [paper]
- 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]
- 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]
- 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]
- 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]
- 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]
- 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]
- 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]
- Antonio Jimeno-Yepes, Jianbin Tang, Benjamin Scott Mashford
"Improving Classification Accuracy of Feedforward Neural Networks for Spiking Neuromorphic Chips". [paper]
- 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]
- 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]