seongsikpark / SNN-neural-coding
Deep SNNs with various neural coding methods (rate, phase, burst, TTFS)
☆10Updated 3 years ago
Alternatives and similar repositories for SNN-neural-coding:
Users that are interested in SNN-neural-coding are comparing it to the libraries listed below
- ☆17Updated 2 years ago
- ☆32Updated last year
- ☆18Updated 3 years ago
- 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 Rate Gradient Approximation Attack Threats Deep Spiking Neural Networks (CVPR 2023)☆16Updated 7 months ago
- CORDIC-SNN, followed with "Unsupervised learning of digital recognition using STDP" published in 2015, frontiers☆23Updated 5 years ago
- FPGA acceleration of a Spike-Timing-Dependent Plasticity learning algorithm for Spiking Neural Networks☆35Updated 4 years ago
- 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
- Framework for radix encoded SNN on FPGA☆13Updated 3 years ago
- ☆38Updated 3 years ago
- MINT, Multiplier-less INTeger Quantization for Energy Efficient Spiking Neural Networks, ASP-DAC 2024, Nominated for Best Paper Award☆12Updated 11 months ago
- Convolutional spiking neural network implementing STDP☆17Updated 2 years ago
- This Pytorch-based framework demonstrates a sentiment analysis task in the IMDB movie reviews dataset using an SNN with a statistic memri…☆20Updated 2 years ago
- Reimplementation of the paper "STDP-based spiking deep convolutional neural networks for object recognition"☆13Updated last year
- ☆12Updated 2 years ago
- CS4362 - Hardware Description Languages. Implemented SNN on an FPGA for real-time image processing using VHDL☆16Updated last year
- Neural Architecture Search for Spiking Neural Networks, ECCV2022☆66Updated 2 years ago
- Code for DCT_SNN, an input encoding scheme for SNNs using DCT☆16Updated 3 years ago
- Code for the ISCAS23 paper "The Hardware Impact of Quantization and Pruning for Weights in Spiking Neural Networks"☆11Updated last year
- [NeurIPS 2024] Advancing Training Efficiency of Deep Spiking Neural Networks through Rate-based Backpropagation☆14Updated 2 months ago
- Pytorch implementation of SEENN (Spiking Early Exit Neural Networks) (NeurIPS 2023)☆14Updated 4 months ago
- ☆14Updated 5 years ago
- Ternary Spike: Learning Ternary Spikes for Spiking Neural Networks☆19Updated last year
- Optimizing threshold and leak in LIF neurons with end-to-end backpropagation☆18Updated 3 years ago
- Pytorch implementation of Neuromorphic Data Augmentation for SNN, Accepted to ECCV 2022.☆37Updated 2 years ago
- Leaky Integrate and Fire (LIF) model implementation for FPGA☆57Updated last year
- PyTorch Implementation of Exploring Temporal Information Dynamics in Spiking Neural Networks (AAAI23)☆28Updated 2 years ago
- SSTDP is a efficient spiking neural network training framework, which is contributed by Fangxin Liu and Wenbo Zhao.☆34Updated 3 years ago
- Threshold annealing in binarized spiking neural networks☆15Updated 2 years ago
- An energy simulation framework for BPTT-based SNN inference and training.☆15Updated last year