BindsNET: An Open-Source Library Used For Simulating Spiking Neural Networks (SNNs) On CPUs Or GPUs Using PyTorch

If you are a computer scientist specialized in bioinformatics and computational biology and looking for a Python framework for simulating spiking neural networks (SNNs) on CPUs or GPUs using PyTorch Tensor functionality, then you should try this open-source library BindsNET (Biologically Inspired Neural & Dynamical Systems in Networks). BindsNET provides an intuitive and easy path to test ideas while incorporating biological abilities to spiking neuronal networks. It is built together by computer scientists, neurocomputational scientists, and biologists to explore the computational ability of neurons with bio-inspired properties utilizing standard machine learning benchmarks.

Biologically Inspired Neural & Dynamical Systems (BINDS) lab is using BindsNET framework for their ongoing research on applying SNNs to machine learning (ML) and reinforcement learning (RL) problems.

Github: https://github.com/BindsNET/bindsnet

Examples: https://github.com/BindsNET/bindsnet/tree/master/examples

🔥 Recommended Read: Leveraging TensorLeap for Effective Transfer Learning: Overcoming Domain Gaps

Installation

Using pip

BindsNET is available through its git repository. Issue

pip install git+https://github.com/BindsNET/bindsnet.git
https://medium.com/pytorch/bindsnet-72726c208a

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