This is the enhanced vision of Awesome SNN Conference Paper.
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Can we get the best of both Binary Neural Networks and Spiking Neural Networks for Efficient Computer Vision? [paper] [openreview]
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LMUFormer: Low Complexity Yet Powerful Spiking Model With Legendre Memory Units [paper] [arxiv] [paper with code] [code] [openreview]
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Threaten Spiking Neural Networks through Combining Rate and Temporal Information [paper] [openreview]
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TAB: Temporal Accumulated Batch Normalization in Spiking Neural Networks [paper] [openreview]
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Certified Adversarial Robustness for Rate Encoded Spiking Neural Networks [paper] [openreview]
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Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN [paper] [arxiv] [paper with code] [openreview]
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Bayesian Bi-clustering of Neural Spiking Activity with Latent Structures [paper] [arxiv] [openreview]
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Spatio-Temporal Approximation: A Training-Free SNN Conversion for Transformers [paper] [openreview]
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Adaptive deep spiking neural network with global-local learning via balanced excitatory and inhibitory mechanism [paper] [openreview]
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Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings [paper] [arxiv] [paper with code] [code] [openreview]
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Online Stabilization of Spiking Neural Networks [paper] [openreview]
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Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips [paper] [openreview]
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A Progressive Training Framework for Spiking Neural Networks with Learnable Multi-hierarchical Model [paper] [openreview]
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Towards Energy Efficient Spiking Neural Networks: An Unstructured Pruning Framework [paper] [openreview]
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Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks [paper] [arxiv] [paper with code] [code] [openreview]
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A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks [paper] [arxiv] [paper with code] [code] [openreview]
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Enhancing the Robustness of Spiking Neural Networks with Stochastic Gating Mechanisms [paper]
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An Efficient Knowledge Transfer Strategy for Spiking Neural Networks from Static to Event Domain [paper] [arxiv] [paper with code] [code]
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Gated Attention Coding for Training High-Performance and Efficient Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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Efficient Spiking Neural Networks with Sparse Selective Activation for Continual Learning [paper]
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DeblurSR: Event-Based Motion Deblurring under the Spiking Representation [paper] [arxiv] [paper with code] [code]
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Point-to-Spike Residual Learning for Energy-Efficient 3D Point Cloud Classification [paper]
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Finding Visual Saliency in Continuous Spike Stream [paper] [arxiv] [paper with code] [code]
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Enhancing Training of Spiking Neural Network with Stochastic Latency [paper]
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SpikingBERT: Distilling BERT to Train Spiking Language Models Using Implicit Differentiation [paper] [arxiv] [paper with code] [code]
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Shrinking Your TimeStep: Towards Low-Latency Neuromorphic Object Recognition with Spiking Neural Networks [paper] [arxiv]
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Ternary Spike: Learning Ternary Spikes for Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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Spiking NeRF: Representing the Real-World Geometry by a Discontinuous Representation [paper] [arxiv] [paper with code] [code]
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Dynamic Spiking Graph Neural Networks [paper] [arxiv] [paper with code]
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Memory-Efficient Reversible Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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TC-LIF: A Two-Compartment Spiking Neuron Model for Long-Term Sequential Modelling [paper] [arxiv] [paper with code] [code]
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Enhancing Representation of Spiking Neural Networks via Similarity-Sensitive Contrastive Learning [paper]
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Dynamic Reactive Spiking Graph Neural Network [paper]
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Evolving Connectivity for Recurrent Spiking Neural Networks [paper] [arxiv] [paper with code] [openreview]
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SparseProp: Efficient Event-Based Simulation and Training of Sparse Recurrent Spiking Neural Networks [paper] [arxiv] [paper with code] [code] [openreview]
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Temporal Conditioning Spiking Latent Variable Models of the Neural Response to Natural Visual Scenes [paper] [arxiv] [paper with code] [openreview]
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Meta-learning families of plasticity rules in recurrent spiking networks using simulation-based inference [paper] [openreview]
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Learning in the Presence of Low-dimensional Structure: A Spiked Random Matrix Perspective [paper] [openreview]
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Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension [paper] [arxiv] [paper with code] [code] [openreview]
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EICIL: Joint Excitatory Inhibitory Cycle Iteration Learning for Deep Spiking Neural Networks [paper] [openreview]
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Spiking PointNet: Spiking Neural Networks for Point Clouds [paper] [arxiv] [paper with code] [code] [openreview]
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Parallel Spiking Neurons with High Efficiency and Ability to Learn Long-term Dependencies [paper] [arxiv] [paper with code] [code] [openreview]
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Enhancing Adaptive History Reserving by Spiking Convolutional Block Attention Module in Recurrent Neural Networks [paper] [arxiv] [paper with code] [openreview]
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Addressing the speed-accuracy simulation trade-off for adaptive spiking neurons [paper] [arxiv] [paper with code] [code] [openreview]
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SEENN: Towards Temporal Spiking Early Exit Neural Networks [paper] [arxiv] [paper with code] [code] [openreview]
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Spike-driven Transformer [paper] [arxiv] [paper with code] [code] [openreview]
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SPQR: Controlling Q-ensemble Independence with Spiked Random Model for Reinforcement Learning [paper] [arxiv] [paper with code] [code] [openreview]
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Exploring Loss Functions for Time-based Training Strategy in Spiking Neural Networks [paper] [paper with code] [code] [openreview]
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Bayesian nonparametric (non-)renewal processes for analyzing neural spike train variability [paper] [openreview]
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Enhancing Motion Deblurring in High-Speed Scenes with Spike Streams [paper] [openreview]
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Trial matching: capturing variability with data-constrained spiking neural networks [paper] [arxiv] [paper with code] [code] [openreview]
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Optimal Algorithms for the Inhomogeneous Spiked Wigner Model [paper] [arxiv] [paper with code] [openreview]
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Bypassing spike sorting: Density-based decoding using spike localization from dense multielectrode probes [paper] [paper with code] [code] [openreview]
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Neural Data Transformer 2: Multi-context Pretraining for Neural Spiking Activity [paper] [paper with code] [code] [openreview]
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Direct Training of SNN using Local Zeroth Order Method [paper] [paper with code] [code] [openreview]
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Rate Gradient Approximation Attack Threats Deep Spiking Neural Networks [paper] [paper with code] [code]
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Constructing Deep Spiking Neural Networks From Artificial Neural Networks With Knowledge Distillation [paper] [arxiv] [paper with code]
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Bridging the Gap between ANNs and SNNs by Calibrating Offset Spikes [paper] [arxiv] [paper with code] [code] [openreview]
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Heterogeneous Neuronal and Synaptic Dynamics for Spike-Efficient Unsupervised Learning: Theory and Design Principles [paper] [arxiv] [paper with code] [openreview]
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Spiking Convolutional Neural Networks for Text Classification [paper] [openreview]
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Spikformer: When Spiking Neural Network Meets Transformer [paper] [arxiv] [paper with code] [code] [openreview]
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Efficient Converted Spiking Neural Network for 3D and 2D Classification [paper] [paper with code]
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Towards Memory- and Time-Efficient Backpropagation for Training Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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Membrane Potential Batch Normalization for Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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Deep Directly-Trained Spiking Neural Networks for Object Detection [paper] [arxiv] [paper with code] [code]
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Unleashing the Potential of Spiking Neural Networks with Dynamic Confidence [paper] [arxiv] [paper with code]
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Temporal-Coded Spiking Neural Networks with Dynamic Firing Threshold: Learning with Event-Driven Backpropagation [paper] [paper with code]
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Inherent Redundancy in Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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SSF: Accelerating Training of Spiking Neural Networks with Stabilized Spiking Flow [paper] [paper with code]
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RMP-Loss: Regularizing Membrane Potential Distribution for Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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Masked Spiking Transformer [paper] [arxiv] [paper with code] [code]
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Surrogate Module Learning: Reduce the Gradient Error Accumulation in Training Spiking Neural Networks [paper]
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Linear Time GPs for Inferring Latent Trajectories from Neural Spike Trains [paper] [arxiv] [paper with code]
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Adaptive Smoothing Gradient Learning for Spiking Neural Networks [paper] [openreview]
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A Unified Optimization Framework of ANN-SNN Conversion: Towards Optimal Mapping from Activation Values to Firing Rates [paper] [openreview]
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Enhancing Efficient Continual Learning with Dynamic Structure Development of Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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Learnable Surrogate Gradient for Direct Training Spiking Neural Networks [paper]
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A Low Latency Adaptive Coding Spike Framework for Deep Reinforcement Learning [paper] [arxiv]
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Spatial-Temporal Self-Attention for Asynchronous Spiking Neural Networks [paper]
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Spike Count Maximization for Neuromorphic Vision Recognition [paper]
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A New ANN-SNN Conversion Method with High Accuracy, Low Latency and Good Robustness [paper]
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Reducing ANN-SNN Conversion Error through Residual Membrane Potential [paper] [arxiv] [paper with code] [code]
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Deep Spiking Neural Networks with High Representation Similarity Model Visual Pathways of Macaque and Mouse [paper] [arxiv] [paper with code] [code]
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ESL-SNNs: An Evolutionary Structure Learning Strategy for Spiking Neural Networks [paper] [arxiv] [paper with code]
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Complex Dynamic Neurons Improved Spiking Transformer Network for Efficient Automatic Speech Recognition [paper] [arxiv] [paper with code] [code]
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Learning Temporal-Ordered Representation for Spike Streams Based on Discrete Wavelet Transforms [paper]
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SVFI: Spiking-Based Video Frame Interpolation for High-Speed Motion [paper]
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Exploring Temporal Information Dynamics in Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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IM-Loss: Information Maximization Loss for Spiking Neural Networks [paper] [paper with code] [openreview]
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Biologically Inspired Dynamic Thresholds for Spiking Neural Networks [paper] [arxiv] [openreview]
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Emergence of Hierarchical Layers in a Single Sheet of Self-Organizing Spiking Neurons [paper] [openreview]
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Learning Optical Flow from Continuous Spike Streams [paper] [openreview]
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Toward Robust Spiking Neural Network Against Adversarial Perturbation [paper] [arxiv] [paper with code] [openreview]
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Training Spiking Neural Networks with Local Tandem Learning [paper] [arxiv] [paper with code] [code] [openreview]
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Theoretically Provable Spiking Neural Networks [paper] [openreview]
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Bayesian Clustering of Neural Spiking Activity Using a Mixture of Dynamic Poisson Factor Analyzers [paper] [openreview]
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Biologically plausible solutions for spiking networks with efficient coding [paper] [arxiv] [paper with code] [openreview]
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Online Training Through Time for Spiking Neural Networks [paper] [arxiv] [paper with code] [code] [openreview]
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Natural gradient enables fast sampling in spiking neural networks [paper] [openreview]
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Mesoscopic modeling of hidden spiking neurons [paper] [arxiv] [paper with code] [code] [openreview]
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SNN-RAT: Robustness-enhanced Spiking Neural Network through Regularized Adversarial Training [paper] [openreview]
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Differentiable hierarchical and surrogate gradient search for spiking neural networks [paper] [openreview]
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LTMD: Learning Improvement of Spiking Neural Networks with Learnable Thresholding Neurons and Moderate Dropout [paper] [openreview]
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Training Spiking Neural Networks with Event-driven Backpropagation [paper] [openreview]
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Dance of SNN and ANN: Solving binding problem by combining spike timing and reconstructive attention [paper] [arxiv] [paper with code] [code] [openreview]
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GLIF: A Unified Gated Leaky Integrate-and-Fire Neuron for Spiking Neural Networks [paper] [arxiv] [paper with code] [code] [openreview]
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Temporal Effective Batch Normalization in Spiking Neural Networks [paper] [openreview]
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Spiking Transformers for Event-Based Single Object Tracking [paper] [paper with code]
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Brain-Inspired Multilayer Perceptron With Spiking Neurons [paper] [arxiv] [paper with code] [code]
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Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation [paper] [arxiv] [paper with code] [code]
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RecDis-SNN: Rectifying Membrane Potential Distribution for Directly Training Spiking Neural Networks [paper] [paper with code]
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Event-Based Video Reconstruction via Potential-Assisted Spiking Neural Network [paper] [arxiv] [paper with code] [code]
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Optimal ANN-SNN Conversion for High-accuracy and Ultra-low-latency Spiking Neural Networks [paper] [arxiv] [paper with code] [code] [openreview]
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Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting [paper] [arxiv] [paper with code] [code] [openreview]
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Spike-inspired rank coding for fast and accurate recurrent neural networks [paper] [arxiv] [paper with code] [code] [openreview]
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Sequence Approximation using Feedforward Spiking Neural Network for Spatiotemporal Learning: Theory and Optimization Methods [paper] [paper with code] [openreview]
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Neuromorphic Data Augmentation for Training Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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Reducing Information Loss for Spiking Neural Networks [paper] [arxiv]
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Towards Ultra Low Latency Spiking Neural Networks for Vision and Sequential Tasks Using Temporal Pruning [paper]
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Real Spike: Learning Real-Valued Spikes for Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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Exploring Lottery Ticket Hypothesis in Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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Neural Architecture Search for Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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Scalable Spike-and-Slab [paper] [arxiv] [paper with code] [code]
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State Transition of Dendritic Spines Improves Learning of Sparse Spiking Neural Networks [paper]
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Neural Network Poisson Models for Behavioural and Neural Spike Train Data [paper]
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AutoSNN: Towards Energy-Efficient Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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Spiking Graph Convolutional Networks [paper] [arxiv] [paper with code] [code]
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Multi-Level Firing with Spiking DS-ResNet: Enabling Better and Deeper Directly-Trained Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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Efficient and Accurate Conversion of Spiking Neural Network with Burst Spikes [paper] [arxiv] [paper with code] [code]
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Recent Advances and New Frontiers in Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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Signed Neuron with Memory: Towards Simple, Accurate and High-Efficient ANN-SNN Conversion [paper]
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Optimized Potential Initialization for Low-Latency Spiking Neural Networks [paper] [arxiv] [paper with code]
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Multi-Sacle Dynamic Coding Improved Spiking Actor Network for Reinforcement Learning [paper]
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PrivateSNN: Privacy-Preserving Spiking Neural Networks [paper] [arxiv] [paper with code]
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SpikeConverter: An Efficient Conversion Framework Zipping the Gap between Artificial Neural Networks and Spiking Neural Networks [paper]
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Fully Spiking Variational Autoencoder [paper] [arxiv] [paper with code] [code]
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Spiking Neural Networks with Improved Inherent Recurrence Dynamics for Sequential Learning [paper] [arxiv] [paper with code] [code]
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Self-Supervised Learning of Event-Based Optical Flow with Spiking Neural Networks [paper] [arxiv] [paper with code] [openreview]
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Sparse Spiking Gradient Descent [paper] [arxiv] [paper with code] [code] [openreview]
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A universal probabilistic spike count model reveals ongoing modulation of neural variability [paper] [paper with code] [openreview]
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Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State [paper] [arxiv] [paper with code] [code] [openreview]
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Probabilistic Tensor Decomposition of Neural Population Spiking Activity [paper] [paper with code] [code] [openreview]
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Learning to Time-Decode in Spiking Neural Networks Through the Information Bottleneck [paper] [arxiv] [paper with code] [openreview]
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Fitting summary statistics of neural data with a differentiable spiking network simulator [paper] [arxiv] [paper with code] [code] [openreview]
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Deep Residual Learning in Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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Three-dimensional spike localization and improved motion correction for Neuropixels recordings [paper] [paper with code] [openreview]
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Differentiable Spike: Rethinking Gradient-Descent for Training Spiking Neural Networks [paper] [paper with code] [openreview]
- Spk2ImgNet: Learning To Reconstruct Dynamic Scene From Continuous Spike Stream [paper] [paper with code]
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Efficient Inference of Flexible Interaction in Spiking-neuron Networks [paper] [arxiv] [paper with code] [openreview]
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Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks [paper] [arxiv] [paper with code] [code] [openreview]
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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]
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DCT-SNN: Using DCT To Distribute Spatial Information Over Time for Low-Latency Spiking Neural Networks [paper] [arxiv] [paper with code]
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Super Resolve Dynamic Scene From Continuous Spike Streams [paper] [paper with code]
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Incorporating Learnable Membrane Time Constant To Enhance Learning of Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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Temporal-Wise Attention Spiking Neural Networks for Event Streams Classification [paper] [arxiv] [paper with code]
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Detection of Signal in the Spiked Rectangular Models [paper] [arxiv] [paper with code]
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A Differentiable Point Process with Its Application to Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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A Free Lunch From ANN: Towards Efficient, Accurate Spiking Neural Networks Calibration [paper] [arxiv] [paper with code] [code]
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Backpropagated Neighborhood Aggregation for Accurate Training of Spiking Neural Networks [paper] [arxiv] [paper with code]
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Pruning of Deep Spiking Neural Networks through Gradient Rewiring [paper] [arxiv] [paper with code] [code]
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Event-based Action Recognition Using Motion Information and Spiking Neural Networks [paper]
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Optimal ANN-SNN Conversion for Fast and Accurate Inference in Deep Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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Exploiting Spiking Dynamics with Spatial-temporal Feature Normalization in Graph Learning [paper] [arxiv] [paper with code]
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Deep Spiking Neural Network with Neural Oscillation and Spike-Phase Information [paper]
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Strategy and Benchmark for Converting Deep Q-Networks to Event-Driven Spiking Neural Networks [paper] [arxiv] [paper with code]
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Training Spiking Neural Networks with Accumulated Spiking Flow [paper]
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Near Lossless Transfer Learning for Spiking Neural Networks [paper]
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Going Deeper With Directly-Trained Larger Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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Temporal-Coded Deep Spiking Neural Network with Easy Training and Robust Performance [paper] [arxiv] [paper with code] [code]
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Rescuing neural spike train models from bad MLE [paper] [arxiv] [paper with code] [code]
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Minimax Dynamics of Optimally Balanced Spiking Networks of Excitatory and Inhibitory Neurons [paper] [arxiv] [paper with code] [code]
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Estimating Rank-One Spikes from Heavy-Tailed Noise via Self-Avoiding Walks [paper] [arxiv] [paper with code]
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Understanding spiking networks through convex optimization [paper] [paper with code] [code]
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Temporal Spike Sequence Learning via Backpropagation for Deep Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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Point process models for sequence detection in high-dimensional neural spike trains [paper] [arxiv] [paper with code] [code]
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Spike and slab variational Bayes for high dimensional logistic regression [paper] [arxiv] [paper with code]
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All-or-nothing statistical and computational phase transitions in sparse spiked matrix estimation [paper] [arxiv] [paper with code]
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Nonasymptotic Guarantees for Spiked Matrix Recovery with Generative Priors [paper] [arxiv] [paper with code]
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Unifying Activation- and Timing-based Learning Rules for Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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Retina-Like Visual Image Reconstruction via Spiking Neural Model [paper] [paper with code]
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RMP-SNN: Residual Membrane Potential Neuron for Enabling Deeper High-Accuracy and Low-Latency Spiking Neural Network [paper] [arxiv] [paper with code] [code]
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Spike-based causal inference for weight alignment [paper] [arxiv] [paper with code] [code] [openreview]
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SpikeGrad: An ANN-equivalent Computation Model for Implementing Backpropagation with Spikes [paper] [arxiv] [paper with code] [openreview]
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Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation [paper] [arxiv] [paper with code] [code] [openreview]
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Deep Spiking Neural Network: Energy Efficiency Through Time based Coding [paper]
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Spike-FlowNet: Event-based Optical Flow Estimation with Energy-Efficient Hybrid Neural Networks [paper] [arxiv]
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Inherent Adversarial Robustness of Deep Spiking Neural Networks: Effects of Discrete Input Encoding and Non-Linear Activations [paper] [arxiv]
- Efficient Non-conjugate Gaussian Process Factor Models for Spike Count Data using Polynomial Approximations [paper] [arxiv] [paper with code]
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LISNN: Improving Spiking Neural Networks with Lateral Interactions for Robust Object Recognition [paper]
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Exploiting Neuron and Synapse Filter Dynamics in Spatial Temporal Learning of Deep Spiking Neural Network [paper] [arxiv] [paper with code] [code]
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Deep Spiking Delayed Feedback Reservoirs and Its Application in Spectrum Sensing of MIMO-OFDM Dynamic Spectrum Sharing [paper]
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Effective AER Object Classification Using Segmented Probability-Maximization Learning in Spiking Neural Networks [paper] [arxiv] [paper with code]
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Biologically Plausible Sequence Learning with Spiking Neural Networks [paper] [arxiv] [paper with code]
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New Efficient Multi-Spike Learning for Fast Processing and Robust Learning [paper]
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Spiking-YOLO: Spiking Neural Network for Energy-Efficient Object Detection [paper] [arxiv] [paper with code]
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The spiked matrix model with generative priors [paper] [arxiv] [paper with code] [code]
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Enabling hyperparameter optimization in sequential autoencoders for spiking neural data [paper] [arxiv] [paper with code] [code]
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Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference [paper] [arxiv] [paper with code] [code]
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Spike-Train Level Backpropagation for Training Deep Recurrent Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models [paper] [paper with code] [code]
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Weak Detection of Signal in the Spiked Wigner Model [paper]
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Bayesian Joint Spike-and-Slab Graphical Lasso [paper] [arxiv] [paper with code] [code]
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Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models [paper] [arxiv]
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STCA: Spatio-Temporal Credit Assignment with Delayed Feedback in Deep Spiking Neural Networks [paper]
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Fast and Accurate Classification with a Multi-Spike Learning Algorithm for Spiking Neurons [paper]
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Direct Training for Spiking Neural Networks: Faster, Larger, Better [paper] [arxiv] [paper with code]
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TDSNN: From Deep Neural Networks to Deep Spike Neural Networks with Temporal-Coding [paper]
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MPD-AL: An Efficient Membrane Potential Driven Aggregate-Label Learning Algorithm for Spiking Neurons [paper]
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Implementation of Boolean AND and OR Logic Gates with Biologically Reasonable Time Constants in Spiking Neural Networks [paper]
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Gradient Descent for Spiking Neural Networks [paper] [arxiv]
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Hybrid Macro/Micro Level Backpropagation for Training Deep Spiking Neural Networks [paper] [arxiv] [paper with code] [code]
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SLAYER: Spike Layer Error Reassignment in Time [paper] [arxiv] [paper with code] [code]
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Long short-term memory and Learning-to-learn in networks of spiking neurons [paper] [arxiv] [paper with code] [code]
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Temporal alignment and latent Gaussian process factor inference in population spike trains [paper] [paper with code]
- Temporally Efficient Deep Learning with Spikes [paper] [arxiv] [paper with code] [code] [openreview]
- Non-linear motor control by local learning in spiking neural networks [paper] [arxiv] [paper with code] [code]