rockpool
SNN framework
A Python library for building and deploying signal processing applications with spiking neural networks on various hardware platforms.
A machine learning library for spiking neural networks. Supports training with both torch and jax pipelines, and deployment to neuromorphic hardware.
55 stars
4 watching
13 forks
Language: Python
last commit: almost 2 years agoLinked from 1 awesome list
deploymentjaxmachine-learningneuromorphicpytorchsnn
Related projects:
| Repository | Description | Stars |
|---|---|---|
| A deep learning library for training and deploying spiking neural networks using PyTorch. | 83 | |
| Deep learning framework for spiking neural networks | 685 | |
| A software package for simulating spiking neural networks using PyTorch. | 1,517 | |
| A Python package for training spiking neural networks with gradient-based learning | 1,383 | |
| A JAX-based library for training and utilizing spiking neural networks | 104 | |
| A framework for building and simulating efficient spiking neural networks on GPU | 220 | |
| An implementation of neural network components and optimization methods for text analysis, including rationales for neural predictions. | 355 | |
| An accelerator designed to speed up spiking neural networks by integrating synaptic weights on a single chip. | 132 | |
| A collection of libraries for building and training neural networks in various programming languages | 70 | |
| Provides a common codebase for simulating neural networks on SpiNNaker hardware | 105 | |
| A deep learning framework designed to improve the performance of Graph Neural Networks (GNNs) through distance encoding techniques. | 184 | |
| Implementation of neural network exploration with randomly wired architectures | 685 | |
| A PyTorch package implementing multi-task deep neural networks for natural language understanding | 2,238 | |
| An implementation of Neural Turing Machine and Differentiable Neural Computer architectures using PyTorch and Visdom for deep learning tasks. | 278 | |
| A Python library for implementing and training various neural network architectures | 40 |