m4urin / quantized-liquid-state-machines
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.☆51Updated 3 years ago
- A Spiking Neural Network model for Digit Recognition using the N-MNIST dataset.☆19Updated 4 years ago
- The code associated with Comparing SNNs and RNNs on neuromorphic vision datasets: Similarities and differences.☆52Updated 3 years ago
- Meta-Dynamic Neurons improved Spatio-temporal Generalization of Spiking Neural Networks☆9Updated 4 years ago
- Reimplementation of the paper "STDP-based spiking deep convolutional neural networks for object recognition"☆13Updated 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
- a spiking neural network module, tempotron for classification☆17Updated 4 years ago
- Neuromorphic paper list, automatically updating everyday at 8:00 am GMT.☆41Updated this week
- ☆9Updated 4 years ago
- A simple from scratch implementation of a Spiking-Neural-Network with STDP in Python which is beeing trained on MNIST.☆40Updated 8 months ago
- ☆45Updated 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
- Pure python implementation of unsupervised MNIST classification using Spiking Neural Networks (using STDP)☆28Updated 3 years ago
- Python2 / Brian2 implementation (attempt) of Normalized Approximate Descent based Supervised Learning Rule.☆12Updated 2 years ago
- Accurate and efficient Spiking recurrent networks on ECG,SHD,SSC,SOLI,(p)SMNIST,TIMIT☆81Updated 2 years ago
- Repository for the master thesis titled "Local Unsupervised Learning of Multimodal Event-Based Data with Spiking Neural Networks", by Jul…☆23Updated 2 years ago
- ☆30Updated 4 months ago
- ☆90Updated last year
- 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
- Training spiking networks with hybrid ann-snn conversion and spike-based backpropagation☆100Updated 4 years ago
- Convolutional spiking neural network implementing voltage-dependent synaptic plasticity and single-spike integrate-and-fire neurons☆12Updated 2 years ago
- A simple direct training implement for SNNs using Spatio-Temporal Backpropagation☆85Updated 2 years ago
- Threshold annealing in binarized spiking neural networks☆16Updated 2 years ago
- Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks☆33Updated 3 years ago
- ☆13Updated 4 years ago
- FeedForward Propagation Through Time on Spiking Neural Network (SNNs)☆53Updated 2 years ago
- Spiking Convolutional Neural Networks☆68Updated 6 years ago
- Neuron-Astrocyte Liquid State Machine☆19Updated 3 years ago
- Plugin for Sinabs, implementing the EXODUS algorithm for training SNNs efficiently with BPTT☆27Updated last month