HuuYuLong / Complementary-LIF
Offical Implementation of "CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks" (ICML 2024 spotlight)
☆17Updated last month
Alternatives and similar repositories for Complementary-LIF:
Users that are interested in Complementary-LIF are comparing it to the libraries listed below
- Ternary Spike: Learning Ternary Spikes for Spiking Neural Networks☆19Updated last year
- STSC-SNN: Spatio-Temporal Synaptic Connection with temporal convolution and attention for spiking neural networks☆22Updated 2 years ago
- [NeurIPS 2024] Advancing Training Efficiency of Deep Spiking Neural Networks through Rate-based Backpropagation☆14Updated 2 months ago
- ☆29Updated last year
- Advancing Spiking Neural Networks towards Deep Residual Learning☆48Updated last year
- GLIF: A Unified Gated Leaky Integrate-and-Fire Neuron for Spiking Neural Networks, NeurIPS 2022 Poster☆51Updated 2 years ago
- Offical implementation of "Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training" (IEEE T-PAMI2025)☆51Updated this week
- Offical implementation of "Attention Spiking Neural Networks" (IEEE T-PAMI2023)☆75Updated 10 months ago
- PyTorch Implementation of Exploring Temporal Information Dynamics in Spiking Neural Networks (AAAI23)☆28Updated 2 years ago
- Reimplementation of the paper "STDP-based spiking deep convolutional neural networks for object recognition"☆13Updated last year
- [ICCV2023] Towards Memory- and Time-Efficient Backpropagation for Training Spiking Neural Networks☆38Updated last year
- SyOPs counter for spiking neural networks☆55Updated last year
- ☆16Updated 2 years ago
- Pytorch implementation of SEENN (Spiking Early Exit Neural Networks) (NeurIPS 2023)☆13Updated 4 months ago
- [ICASSP2022] RATE CODING OR DIRECT CODING: WHICH ONE IS BETTER FOR ACCURATE, ROBUST, and ENERGY-EFFICIENT SPIKING NEURAL NETWORKS☆19Updated last year
- STBP is a way to train SNN with datasets by Backward propagation.Using this Repositories allows you to train SNNS with STBP and quantize …☆28Updated 3 years ago
- [TNNLS 2024] Implementation of "TCJA-SNN: Temporal-Channel Joint Attention for Spiking Neural Networks"☆52Updated 11 months ago
- Pytorch implementation of Neuromorphic Data Augmentation for SNN, Accepted to ECCV 2022.☆37Updated 2 years ago
- ☆16Updated last year
- [NeurIPS 2022] Online Training Through Time for Spiking Neural Networks☆59Updated last year
- ☆51Updated last year
- SATA_Sim is an energy estimation framework for Backpropagation-Through-Time (BPTT) based Spiking Neural Networks (SNNs) training and infe…☆26Updated 6 months ago
- Codes of the paper: Towards Energy Efficient Spiking Neural Networks: An Unstructured Pruning Framework (ICLR2024)☆10Updated last year
- Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks☆34Updated 3 years ago
- ☆25Updated 2 years ago
- An event-driven learning algorithm for spiking neural networks☆25Updated 10 months ago
- A simple direct training implement for SNNs using Spatio-Temporal Backpropagation☆85Updated last year
- Neural Architecture Search for Spiking Neural Networks, ECCV2022☆66Updated 2 years ago
- Create a new backward path for more accurate SNN gradients.☆16Updated 7 months ago
- ☆60Updated last year