m4urin / quantized-liquid-state-machinesLinks
A Liquid State Machine using quantized neurons that are operating on lower-bit representations and fixed point computations. It provides a next step towards the implementation of efficient accelerators that can be used in the field of neuromorphic computing.
☆14Updated last year
Alternatives and similar repositories for quantized-liquid-state-machines
Users that are interested in quantized-liquid-state-machines are comparing it to the libraries listed below
Sorting:
- Codes of the paper of "Surrogate-Assisted Evolutionary Search of Spiking Neural Architectures in Liquid State Machines"☆12Updated 2 years ago
- PyTorch implementation of the eligibility propagation (e-prop) learning algorithm.☆52Updated 3 years ago
- Python2 / Brian2 implementation (attempt) of Normalized Approximate Descent based Supervised Learning Rule.☆12Updated 2 years ago
- Threshold annealing in binarized spiking neural networks☆16Updated 3 years ago
- A simple from scratch implementation of a Spiking-Neural-Network with STDP in Python which is beeing trained on MNIST.☆41Updated 9 months ago
- Neuron-Astrocyte Liquid State Machine☆19Updated 3 years ago
- ☆9Updated 4 years ago
- FeedForward Propagation Through Time on Spiking Neural Network (SNNs)☆55Updated 2 years ago
- Convolutional spiking neural network implementing voltage-dependent synaptic plasticity and single-spike integrate-and-fire neurons☆13Updated 2 years ago
- Meta-Dynamic Neurons improved Spatio-temporal Generalization of Spiking Neural Networks☆9Updated 4 years ago
- PyTorch Implementation of Online Training of Spiking Recurrent Neural Networks with Phase-Change Memory Synapses☆20Updated 3 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 …☆29Updated 3 years ago
- a spiking neural network module, tempotron for classification☆17Updated 4 years ago
- ☆45Updated 2 years ago
- The code associated with Comparing SNNs and RNNs on neuromorphic vision datasets: Similarities and differences.☆52Updated 3 years ago
- A Spiking Neural Network model for Digit Recognition using the N-MNIST dataset.☆19Updated 4 years ago
- Training spiking networks with hybrid ann-snn conversion and spike-based backpropagation☆100Updated 4 years ago
- Datasets recorded from Neuromorphic Sensors or Conversions using Simulations of Sensors☆31Updated last year
- Repository for the master thesis titled "Local Unsupervised Learning of Multimodal Event-Based Data with Spiking Neural Networks", by Jul…☆24Updated 2 weeks ago
- Plugin for Sinabs, implementing the EXODUS algorithm for training SNNs efficiently with BPTT☆27Updated 2 months ago
- Tutorial for surrogate gradient learning in spiking neural networks☆46Updated 11 months ago
- Pytorch implementation of TSSL-BP rule for Deep Spiking Neural Networks.☆71Updated last year
- Accurate and efficient Spiking recurrent networks on ECG,SHD,SSC,SOLI,(p)SMNIST,TIMIT☆81Updated 2 years ago
- Code for the model presented in the paper "A Biologically Plausible Supervised Learning Method for Spiking Neural Networks Using the Symm…☆47Updated 4 years ago
- A simple direct training implement for SNNs using Spatio-Temporal Backpropagation☆87Updated 2 years ago
- ☆91Updated last year
- Optimizing threshold and leak in LIF neurons with end-to-end backpropagation☆19Updated 3 years ago
- SSTDP is a efficient spiking neural network training framework, which is contributed by Fangxin Liu and Wenbo Zhao.☆34Updated 3 years ago
- This repository will host models, modules, algorithms and applications developed by the INRC Community to run on the Intel Loihi Platform…☆83Updated last year
- Collect important papers about snn☆32Updated 3 years ago