Skip to content

Latest commit

 

History

History
1024 lines (523 loc) · 95.8 KB

README.md

File metadata and controls

1024 lines (523 loc) · 95.8 KB

Awesome SNN Conference Paper Awesome

🔥 This repo collects top international conference papers, codes about Spiking Neural Networks for anyone who wants to do research on it. We are continuously improving the project.

The part of 2018-2021 is referenced in Awesome-SNN-Paper-Collection.

The part of 2022 is referenced in 2022年顶会、顶刊SNN相关论文.

Thank the repo or blogs for their contributions to the collection of papers from top conferences or top journals in the SNN field.

🤗 Welcome anyone who is interested to contribute to the repo together ! If you find another papers that are not in this repo, you can pull requests.

❤Thanks so much @Ruichen0424 for the collaboration!


Table of Contents (Conferences by Year)
  1. 2024
  2. 2023
  3. 2022
  4. 2021
  5. 2020
  6. 2019
  7. 2018

Abbreviation - Full Name List

Abbreviation Full Name
CVPR IEEE Conference on Computer Vision and Pattern Recognition
ICCV IEEE International Conference on Computer Vision
NeurIPS Conference on Neural Information Processing Systems
AAAI Association for the Advancement of Artificial Intelligence
ICLR International Conference on Learning Representations
ICML International Conference on Machine Learning
IJCAI International Joint Conference on Artificial Intelligence
ICASSP IEEE International Conference on Acoustics, Speech and Signal Processing
IJCNN International Joint Conference on Neural Networks
PAMI IEEE Transactions on Pattern Analysis and Machine Intelligence
TNNLS IEEE Transactions on Neural Networks and Learning Systems

2024

NeurIPS-2024

  • Latent Diffusion for Neural Spiking Data [paper] [arxiv] [paper with code]

  • Spiking Transformer with Experts Mixture [paper]

  • Autonomous Driving with Spiking Neural Networks [paper] [arxiv] [paper with code] [code]

  • Rethinking the Dynamics of Spiking Neural Networks [paper]

  • Spiking Graph Neural Network on Riemannian Manifolds [paper] [arxiv] [paper with code] [code]

  • Spiking Neural Network as Adaptive Event Stream Slicer [paper] [arxiv] [paper with code]

  • Spike-based Neuromorphic Model for Sound Source Localization [paper]

  • QKFormer: Hierarchical Spiking Transformer using Q-K Attention [paper] [arxiv] [paper with code] [code]

  • Exact Gradients for Stochastic Spiking Neural Networks Driven by Rough Signals [paper] [arxiv] [paper with code]

  • Neuronal Competition Groups with Supervised STDP for Spike-Based Classification [paper] [arxiv] [paper with code]

  • Slack-Free Spiking Neural Network Formulation for Hypergraph Minimum Vertex Cover [paper]

  • Continuous Spatiotemporal Events Decoupling through Spike-based Bayesian Computation [paper]

  • SpikeReveal: Unlocking Temporal Sequences from Real Blurry Inputs with Spike Streams [paper] [arxiv] [paper with code] [code]

  • Spiking Token Mixer: A event-driven friendly Former structure for spiking neural networks [paper]

  • Spatio-Temporal Interactive Learning for Efficient Image Reconstruction of Spiking Cameras [paper]

  • Advancing Spiking Neural Networks for Sequential Modeling through Central Pattern Generators [paper]

  • Take A Shortcut Back: Mitigating the Gradient Vanishing for Training Spiking Neural Networks [paper] [arxiv] [paper with code]

  • Towards a "Universal Translator" for Neural Dynamics at Single-Cell, Single-Spike Resolution [paper] [arxiv] [paper with code]

  • FEEL-SNN: Robust Spiking Neural Networks with Frequency Encoding and Evolutionary Leak Factor [paper]

  • EnOF: Training Accurate Spiking Neural Networks via Enhancing the Output Feature Representation [paper]

  • Advancing Training Efficiency of Deep Spiking Neural Networks through Rate-based Backpropagation [paper] [arxiv] [paper with code] [code]

  • Statistical Estimation in the Spiked Tensor Model via the Quantum Approximate Optimization Algorithm [paper]

  • SpGesture: Source-Free Domain-adaptive sEMG-based Gesture Recognition with Jaccard Attentive Spiking Neural Network [paper] [arxiv] [paper with code] [code]

  • Long-Range Feedback Spiking Network Captures Dynamic and Static Representations of the Visual Cortex under Movie Stimuli [paper]

  • SpikedAttention: Training-Free and Fully Spike-Driven Transformer-to-SNN Conversion with Winner-Oriented Spike Shift for Softmax Operation [paper]

IJCAI-2024

  • Learning a Spiking Neural Network for Efficient Image Deraining [arxiv] [paper with code] [code]

  • LitE-SNN: Designing Lightweight and Efficient Spiking Neural Network through Spatial-Temporal Compressive Network Search and Joint Optimization [arxiv] [paper with code]

  • TIM: An Efficient Temporal Interaction Module for Spiking Transformer [arxiv] [paper with code] [code]

  • One-step Spiking Transformer with a Linear Complexity

  • EC-SNN: Splitting Deep Spiking Neural Networks for Edge Devices

  • Apprenticeship-Inspired Elegance: Synergistic Knowledge Distillation Empowers Spiking Neural Networks for Efficient Single-Eye Emotion Recognition [arxiv] [paper with code]

ICML-2024

  • CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks [paper] [arxiv] [paper with code] [code]

  • High-Performance Temporal Reversible Spiking Neural Networks with O(L) Training Memory and O(1) Inference Cost [paper]

  • SpikeZIP-TF: Conversion is All You Need for Transformer-based SNN [paper] [arxiv] [paper with code] [code]

  • NDOT: Neuronal Dynamics-based Online Training for Spiking Neural Networks [paper]

  • Towards Efficient Spiking Transformer: a Token Sparsification Framework for Training and Inference Acceleration [paper]

  • Efficient and Effective Time-Series Forecasting with Spiking Neural Networks [paper] [arxiv] [paper with code] [code]

  • Balanced Resonate-and-Fire Neurons [paper]

  • SpikeLM: Towards General Spike-Driven Language Modeling via Elastic Bi-Spiking Mechanisms [paper] [arxiv] [paper with code] [code]

  • Robust Stable Spiking Neural Networks [paper] [arxiv] [paper with code] [code]

  • Conditionally-Conjugate Gaussian Process Factor Analysis for Spike Count Data via Data Augmentation [paper]

  • Towards efficient deep spiking neural networks construction with spiking activity based pruning [paper]

  • Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning [paper] [arxiv] [paper with code] [code]

  • Sign Gradient Descent-based Neuronal Dynamics: ANN-to-SNN Conversion Beyond ReLU Network [paper] [arxiv] [paper with code] [code]

  • Autaptic Synaptic Circuit Enhances Spatio-temporal Predictive Learning of Spiking Neural Networks [paper] [arxiv] [paper with code] [code]

  • Enhancing Adversarial Robustness in SNNs with Sparse Gradients [paper]

AAAI-2024

  • Enhancing the Robustness of Spiking Neural Networks with Stochastic Gating Mechanisms [paper]

  • An Efficient Knowledge Transfer Strategy for Spiking Neural Networks from Static to Event Domain [paper] [arxiv] [paper with code] [code]

  • Gated Attention Coding for Training High-Performance and Efficient Spiking Neural Networks [paper] [arxiv] [paper with code] [code]

  • Efficient Spiking Neural Networks with Sparse Selective Activation for Continual Learning [paper]

  • DeblurSR: Event-Based Motion Deblurring under the Spiking Representation [paper] [arxiv] [paper with code] [code]

  • Point-to-Spike Residual Learning for Energy-Efficient 3D Point Cloud Classification [paper]

  • Finding Visual Saliency in Continuous Spike Stream [paper] [arxiv] [paper with code] [code]

  • Enhancing Training of Spiking Neural Network with Stochastic Latency [paper]

  • SpikingBERT: Distilling BERT to Train Spiking Language Models Using Implicit Differentiation [paper] [arxiv] [paper with code] [code]

  • Shrinking Your TimeStep: Towards Low-Latency Neuromorphic Object Recognition with Spiking Neural Networks [paper] [arxiv]

  • Ternary Spike: Learning Ternary Spikes for Spiking Neural Networks [paper] [arxiv] [paper with code] [code]

  • Spiking NeRF: Representing the Real-World Geometry by a Discontinuous Representation [paper] [arxiv] [paper with code] [code]

  • Dynamic Spiking Graph Neural Networks [paper] [arxiv] [paper with code]

  • Memory-Efficient Reversible Spiking Neural Networks [paper] [arxiv] [paper with code] [code]

  • TC-LIF: A Two-Compartment Spiking Neuron Model for Long-Term Sequential Modelling [paper] [arxiv] [paper with code] [code]

  • Enhancing Representation of Spiking Neural Networks via Similarity-Sensitive Contrastive Learning [paper]

  • Dynamic Reactive Spiking Graph Neural Network [paper]

  • Transient Glimpses: Unveiling Occluded Backgrounds through the Spike Camera [paper]

  • Joint Demosaicing and Denoising for Spike Camera [paper]

  • Recognizing Ultra-High-Speed Moving Objects with Bio-Inspired Spike Camera [paper]

  • Optical Flow for Spike Camera with Hierarchical Spatial-Temporal Spike Fusion [paper]

  • Exploiting Symmetric Temporally Sparse BPTT for Efficient RNN Training [paper]

ICLR-2024

  • Can we get the best of both Binary Neural Networks and Spiking Neural Networks for Efficient Computer Vision? [paper] [openreview]

  • LMUFormer: Low Complexity Yet Powerful Spiking Model With Legendre Memory Units [paper] [arxiv] [paper with code] [code] [openreview]

  • Threaten Spiking Neural Networks through Combining Rate and Temporal Information [paper] [openreview]

  • TAB: Temporal Accumulated Batch Normalization in Spiking Neural Networks [paper] [openreview]

  • Certified Adversarial Robustness for Rate Encoded Spiking Neural Networks [paper] [openreview]

  • Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN [paper] [arxiv] [paper with code] [openreview]

  • Bayesian Bi-clustering of Neural Spiking Activity with Latent Structures [paper] [arxiv] [openreview]

  • Spatio-Temporal Approximation: A Training-Free SNN Conversion for Transformers [paper] [openreview]

  • Adaptive deep spiking neural network with global-local learning via balanced excitatory and inhibitory mechanism [paper] [openreview]

  • Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings [paper] [arxiv] [paper with code] [code] [openreview]

  • Online Stabilization of Spiking Neural Networks [paper] [openreview]

  • Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips [paper] [openreview]

  • A Progressive Training Framework for Spiking Neural Networks with Learnable Multi-hierarchical Model [paper] [openreview]

  • Towards Energy Efficient Spiking Neural Networks: An Unstructured Pruning Framework [paper] [openreview]

  • Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks [paper] [arxiv] [paper with code] [code] [openreview]

  • A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks [paper] [arxiv] [paper with code] [code] [openreview]

  • SpikePoint: An Efficient Point-based Spiking Neural Network for Event Cameras Action Recognition [paper] [arxiv] [paper with code] [openreview]

  • EventRPG: Event Data Augmentation with Relevance Propagation Guidance [paper] [code]

CVPR-2024

  • SpikingResformer: Bridging ResNet and Vision Transformer in Spiking Neural Networks [paper] [code]

  • Are Conventional SNNs Really Efficient? A Perspective from Network Quantization [paper]

  • SFOD: Spiking Fusion Object Detector [paper] [code]

ICASSP-2024

  • sVAD: A Robust, Low-Power, and Light-Weight Voice Activity Detection with Spiking Neural Networks [paper]

  • Optimal ANN-SNN Conversion with Group Neurons [paper] [code]

PAMI-2024

TNNLS-2024

  • Advancing Spiking Neural Networks Toward Deep Residual Learning [paper] [arxiv] [paper with code] [code]

  • Adaptive Synaptic Scaling in Spiking Networks for Continual Learning and Enhanced Robustness [paper]

  • Spiking Neural Network for Ultralow-Latency and High-Accurate Object Detection [paper]

  • TCJA-SNN: Temporal-Channel Joint Attention for Spiking Neural Networks [paper] [arxiv] [paper with code] [code]

  • Fully Spiking Actor Network With Intralayer Connections for Reinforcement Learning [paper]

  • Minicolumn-Based Episodic Memory Model With Spiking Neurons, Dendrites and Delays [paper]

  • Efficient Deep Spiking Multilayer Perceptrons With Multiplication-Free Inference [paper]

  • CDNA-SNN: A New Spiking Neural Network for Pattern Classification Using Neuronal Assemblies [paper]

2023

ICCV-2023

CVPR-2023

NeurIPS-2023

AAAI-2023

  • Reducing ANN-SNN Conversion Error through Residual Membrane Potential [paper] [arxiv] [paper with code] [code]

  • Deep Spiking Neural Networks with High Representation Similarity Model Visual Pathways of Macaque and Mouse [paper] [arxiv] [paper with code] [code]

  • ESL-SNNs: An Evolutionary Structure Learning Strategy for Spiking Neural Networks [paper] [arxiv] [paper with code]

  • Complex Dynamic Neurons Improved Spiking Transformer Network for Efficient Automatic Speech Recognition [paper] [arxiv] [paper with code] [code]

  • Learning Temporal-Ordered Representation for Spike Streams Based on Discrete Wavelet Transforms [paper]

  • SVFI: Spiking-Based Video Frame Interpolation for High-Speed Motion [paper]

  • Exploring Temporal Information Dynamics in Spiking Neural Networks [paper] [arxiv] [paper with code] [code]

  • Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks [paper] [arxiv] [paper with code] [code]

  • Self-Supervised Joint Dynamic Scene Reconstruction and Optical Flow Estimation for Spiking Camera [paper]

  • Learning to Super-resolve Dynamic Scenes for Neuromorphic Spike Camera [paper]

  • Astromorphic Self-Repair of Neuromorphic Hardware Systems [paper]

ICML-2023

  • Surrogate Module Learning: Reduce the Gradient Error Accumulation in Training Spiking Neural Networks [paper]

  • Linear Time GPs for Inferring Latent Trajectories from Neural Spike Trains [paper] [arxiv] [paper with code]

  • Adaptive Smoothing Gradient Learning for Spiking Neural Networks [paper] [openreview]

  • A Unified Optimization Framework of ANN-SNN Conversion: Towards Optimal Mapping from Activation Values to Firing Rates [paper] [openreview]

ICLR-2023

IJCAI-2023

  • Enhancing Efficient Continual Learning with Dynamic Structure Development of Spiking Neural Networks [paper] [arxiv] [paper with code] [code]

  • Learnable Surrogate Gradient for Direct Training Spiking Neural Networks [paper]

  • A Low Latency Adaptive Coding Spike Framework for Deep Reinforcement Learning [paper] [arxiv]

  • Spatial-Temporal Self-Attention for Asynchronous Spiking Neural Networks [paper]

  • Spike Count Maximization for Neuromorphic Vision Recognition [paper]

  • A New ANN-SNN Conversion Method with High Accuracy, Low Latency and Good Robustness [paper]

ICASSP-2023

  • Joint ANN-SNN Co-training for Object Localization and Image Segmentation [paper]

  • Adaptive Axonal Delays in feedforward spiking neural networks for accurate spoken word recognition [paper]

  • Training Robust Spiking Neural Networks with ViewPoint Transform and SpatioTemporal Stretching [paper]

  • In-Sensor & Neuromorphic Computing Are all You Need for Energy Efficient Computer Vision [paper]

  • Training Stronger Spiking Neural Networks with Biomimetic Adaptive Internal Association Neurons [paper]

  • Training Robust Spiking Neural Networks on Neuromorphic Data with Spatiotemporal Fragments [paper]

  • Leveraging Sparsity with Spiking Recurrent Neural Networks for Energy-Efficient Keyword Spotting [paper]

IJCNN-2023

  • Brain-Inspired Spiking Neural Network for Online Unsupervised Time Series Prediction [paper]

  • Low Precision Quantization-aware Training in Spiking Neural Networks with Differentiable Quantization Function [paper]

PAMI-2023

  • Fast-SNN: Fast Spiking Neural Network by Converting Quantized ANN [paper] [code]

  • Attention Spiking Neural Networks [paper] [code]

  • CQ+ Training: Minimizing Accuracy Loss in Conversion From Convolutional Neural Networks to Spiking Neural Networks [paper]

TNNLS-2023

  • Attention-Based Deep Spiking Neural Networks for Temporal Credit Assignment Problems [paper]

  • Effective Active Learning Method for Spiking Neural Networks [paper]

  • Backpropagation-Based Learning Techniques for Deep Spiking Neural Networks: A Survey [paper]

Neural Networks-2023

  • SPIDE: A Purely Spike-based Method for Training Feedback Spiking Neural Networks [paper]

2022

CVPR-2022

ECCV-2022

  • Spike Transformer: Monocular Depth Estimation for Spiking Camera [paper]

  • Neuromorphic Data Augmentation for Training Spiking Neural Networks [paper] [arxiv] [paper with code] [code]

  • Reducing Information Loss for Spiking Neural Networks [paper] [arxiv]

  • Towards Ultra Low Latency Spiking Neural Networks for Vision and Sequential Tasks Using Temporal Pruning [paper]

  • Real Spike: Learning Real-Valued Spikes for Spiking Neural Networks [paper] [arxiv] [paper with code] [code]

  • Exploring Lottery Ticket Hypothesis in Spiking Neural Networks [paper] [arxiv] [paper with code] [code]

  • Neural Architecture Search for Spiking Neural Networks [paper] [arxiv] [paper with code] [code]

  • Lottery Ticket Hypothesis for Spiking Neural Networks [paper]

NeurIPS-2022

AAAI-2022

  • Optimized Potential Initialization for Low-Latency Spiking Neural Networks [paper] [arxiv] [paper with code]

  • Multi-Sacle Dynamic Coding Improved Spiking Actor Network for Reinforcement Learning [paper]

  • PrivateSNN: Privacy-Preserving Spiking Neural Networks [paper] [arxiv] [paper with code]

  • SpikeConverter: An Efficient Conversion Framework Zipping the Gap between Artificial Neural Networks and Spiking Neural Networks [paper]

  • Fully Spiking Variational Autoencoder [paper] [arxiv] [paper with code] [code]

  • Spiking Neural Networks with Improved Inherent Recurrence Dynamics for Sequential Learning [paper] [arxiv] [paper with code] [code]

  • Spatio-Temporal Recurrent Networks for Event-Based Optical Flow Estimation [paper] [code]

ICASSP-2022

  • Axonal Delay As a Short-Term Memory for Feed Forward Deep Spiking Neural Networks [paper]

  • Gradual Surrogate Gradient Learning in Deep Spiking Neural Networks [paper]

  • T-NGA: Temporal Network Grafting Algorithm for Learning to Process Spiking Audio Sensor Events [paper]

  • Modeling The Detection Capability Of High-Speed Spiking Cameras [paper]

  • DynSNN: A Dynamic Approach to Reduce Redundancy in Spiking Neural Networks [paper]

  • Optimizing The Consumption Of Spiking Neural Networks With Activity Regularization [paper]

  • Rate Coding Or Direct Coding: Which One Is Better For Accurate, Robust, And Energy-Efficient Spiking Neural Networks? [paper]

  • Motif-Topology and Reward-Learning Improved Spiking Neural Network for Efficient Multi-Sensory Integration [paper]

  • Event-Based Multimodal Spiking Neural Network with Attention Mechanism [paper]

  • A Hybrid Learning Framework for Deep Spiking Neural Networks with One-Spike Temporal Coding [paper]

  • Supervised Training of Siamese Spiking Neural Networks with Earth Mover's Distance [paper]

  • A Time Encoding Approach to Training Spiking Neural Networks [paper]

ICML-2022

  • State Transition of Dendritic Spines Improves Learning of Sparse Spiking Neural Networks [paper]

  • AutoSNN: Towards Energy-Efficient Spiking Neural Networks [paper] [arxiv] [paper with code] [code]

  • Scalable Spike-and-Slab [paper] [arxiv] [paper with code] [code]

  • Neural Network Poisson Models for Behavioural and Neural Spike Train Data [paper]

IJCAI-2022

  • Efficient and Accurate Conversion of Spiking Neural Network with Burst Spikes [paper] [arxiv] [paper with code] [code]

  • Spiking Graph Convolutional Networks [paper] [arxiv] [paper with code] [code]

  • Signed Neuron with Memory: Towards Simple, Accurate and High-Efficient ANN-SNN Conversion [paper] [code]

  • Self-Supervised Mutual Learning for Dynamic Scene Reconstruction of Spiking Camera [paper]

  • Multi-Level Firing with Spiking DS-ResNet: Enabling Better and Deeper Directly-Trained Spiking Neural Networks [paper] [arxiv] [paper with code] [code]

ICLR-2022

IJCNN-2022

  • Event-Driven Tactile Learning with Location Spiking Neurons [paper] [code]

  • Spiking Approximations of the MaxPooling Operation in Deep SNNs [paper] [code]

  • Spikemax: Spike-based Loss Methods for Classification [paper]

  • Object Detection with Spiking Neural Networks on Automotive Event Data [paper] [code]

NEURAL COMPUTATION

  • Training Deep Convolutional Spiking Neural Networks With Spike Probabilistic Global Pooling [paper]

Neural Networks-2022

  • Modeling learnable electrical synapse for high precision spatio-temporal recognition [paper]

IEEE TCYB (IEEE Transactions on Cybernetics)

  • Toward Efficient Processing and Learning With Spikes: New Approaches for Multispike Learning [paper]

2021

NeurIPS-2021

CVPR-2021

  • Spk2ImgNet: Learning To Reconstruct Dynamic Scene From Continuous Spike Stream [paper] [paper with code]

ICLR-2021

ICCV-2021

  • HIRE-SNN: Harnessing the Inherent Robustness of Energy-Efficient Deep Spiking Neural Networks by Training With Crafted Input Noise [paper] [arxiv] [paper with code] [code]

  • DCT-SNN: Using DCT To Distribute Spatial Information Over Time for Low-Latency Spiking Neural Networks [paper] [arxiv] [paper with code]

  • Super Resolve Dynamic Scene From Continuous Spike Streams [paper] [paper with code]

  • Incorporating Learnable Membrane Time Constant To Enhance Learning of Spiking Neural Networks [paper] [arxiv] [paper with code] [code]

  • Temporal-Wise Attention Spiking Neural Networks for Event Streams Classification [paper] [arxiv] [paper with code]

ICML-2021

IJCAI-2021

  • Pruning of Deep Spiking Neural Networks through Gradient Rewiring [paper] [arxiv] [paper with code] [code]

  • Event-based Action Recognition Using Motion Information and Spiking Neural Networks [paper]

  • Optimal ANN-SNN Conversion for Fast and Accurate Inference in Deep Spiking Neural Networks [paper] [arxiv] [paper with code] [code]

  • Exploiting Spiking Dynamics with Spatial-temporal Feature Normalization in Graph Learning [paper] [arxiv] [paper with code]

AAAI-2021

  • Deep Spiking Neural Network with Neural Oscillation and Spike-Phase Information [paper]

  • Strategy and Benchmark for Converting Deep Q-Networks to Event-Driven Spiking Neural Networks [paper] [arxiv] [paper with code]

  • Training Spiking Neural Networks with Accumulated Spiking Flow [paper]

  • Near Lossless Transfer Learning for Spiking Neural Networks [paper]

  • Going Deeper With Directly-Trained Larger Spiking Neural Networks [paper] [arxiv] [paper with code] [code]

  • Temporal-Coded Deep Spiking Neural Network with Easy Training and Robust Performance [paper] [arxiv] [paper with code] [code]

2020

NeurIPS-2020

CVPR-2020

  • Retina-Like Visual Image Reconstruction via Spiking Neural Model [paper] [paper with code]

  • RMP-SNN: Residual Membrane Potential Neuron for Enabling Deeper High-Accuracy and Low-Latency Spiking Neural Network [paper] [arxiv] [paper with code] [code]

ICLR-2020

ECCV-2020

  • Deep Spiking Neural Network: Energy Efficiency Through Time based Coding [paper]

  • Spike-FlowNet: Event-based Optical Flow Estimation with Energy-Efficient Hybrid Neural Networks [paper] [arxiv]

  • Inherent Adversarial Robustness of Deep Spiking Neural Networks: Effects of Discrete Input Encoding and Non-Linear Activations [paper] [arxiv]

ICML-2020

  • Efficient Non-conjugate Gaussian Process Factor Models for Spike Count Data using Polynomial Approximations [paper] [arxiv] [paper with code]

IJCAI-2020

  • LISNN: Improving Spiking Neural Networks with Lateral Interactions for Robust Object Recognition [paper]

  • Exploiting Neuron and Synapse Filter Dynamics in Spatial Temporal Learning of Deep Spiking Neural Network [paper] [arxiv] [paper with code] [code]

AAAI-2020

  • Deep Spiking Delayed Feedback Reservoirs and Its Application in Spectrum Sensing of MIMO-OFDM Dynamic Spectrum Sharing [paper]

  • Effective AER Object Classification Using Segmented Probability-Maximization Learning in Spiking Neural Networks [paper] [arxiv] [paper with code]

  • Biologically Plausible Sequence Learning with Spiking Neural Networks [paper] [arxiv] [paper with code]

  • New Efficient Multi-Spike Learning for Fast Processing and Robust Learning [paper]

  • Spiking-YOLO: Spiking Neural Network for Energy-Efficient Object Detection [paper] [arxiv] [paper with code]

2019

NeurIPS-2019

ICML-2019

  • Weak Detection of Signal in the Spiked Wigner Model [paper]

  • Bayesian Joint Spike-and-Slab Graphical Lasso [paper] [arxiv] [paper with code] [code]

  • Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models [paper] [arxiv]

IJCAI-2019

  • STCA: Spatio-Temporal Credit Assignment with Delayed Feedback in Deep Spiking Neural Networks [paper]

  • Fast and Accurate Classification with a Multi-Spike Learning Algorithm for Spiking Neurons [paper]

AAAI-2019

  • Direct Training for Spiking Neural Networks: Faster, Larger, Better [paper] [arxiv] [paper with code]

  • TDSNN: From Deep Neural Networks to Deep Spike Neural Networks with Temporal-Coding [paper]

  • MPD-AL: An Efficient Membrane Potential Driven Aggregate-Label Learning Algorithm for Spiking Neurons [paper]

  • Implementation of Boolean AND and OR Logic Gates with Biologically Reasonable Time Constants in Spiking Neural Networks [paper]

2018

NeurIPS-2018

ICLR-2018

ICML-2018

IJCAI-2018

  • Jointly Learning Network Connections and Link Weights in Spiking Neural Networks [paper]

  • CSNN: An Augmented Spiking based Framework with Perceptron-Inception [paper]

  • Brain-inspired Balanced Tuning for Spiking Neural Networks [paper]

AAAI-2018

  • A Plasticity-Centric Approach to Train the Non-Differential Spiking Neural Networks [paper]

  • Learning Nonlinear Dynamics in Efficient, Balanced Spiking Networks Using Local Plasticity Rules [paper]

Starchart

Star History Chart