Neuromorphic-Computing-Guide
Learn about the Neumorphic engineering process of creating large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures. (by mikeroyal)
snntorch
Deep and online learning with spiking neural networks in Python (by jeshraghian)
| Neuromorphic-Computing-Guide | snntorch | |
|---|---|---|
| 10 | 2 | |
| 252 | 1,099 | |
| - | - | |
| 5.0 | 9.2 | |
| 4 months ago | 19 days ago | |
| Python | Python | |
| - | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Neuromorphic-Computing-Guide
Posts with mentions or reviews of Neuromorphic-Computing-Guide.
We have used some of these posts to build our list of alternatives
and similar projects.
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I am extremely interested second language acquisition and Artificial intelligence. How can I get into research?
Start reading papers on https://www.biorxiv.org/ and notice what seems most interesting or promising to you. Learn python. There are actually quite a few open source "into to machine learning" courses - maybe start with MIT's Learning Library, see what you find there. I also have this bookmarked for myself for later; I'm sure there are a few more goodies worth checking out here: https://github.com/mikeroyal/Neuromorphic-Computing-Guide
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Getting Started with Neuromorphic Computing
Tools and Resources for getting started with Neumorphic Computing. The process of creating large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures.
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Neuromorphic Engineering
Neuromorphic engineering, which combines electrical, computer, and mechanical engineering with biology, physics, and neuroscience. uses specialized computing architectures that reflect the structure (morphology) of neural networks from the bottom up: dedicated processing units emulate the behavior of neurons directly in hardware, and a web of physical interconnections (bus-systems) facilitate the rapid exchange of information. Useful Tools and Resources for learning about Neuromorphic engineering.
- GitHub - mikeroyal/Neuromorphic-Computing-Guide: Neuromorphic Computing Guide
- Neuromorphic Computing that enables fast and power-efficient neural network–based artificial intelligence
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Neuromorphic Computing
Neuromorphic computing models the way the brain works through spiking neural networks and other types of neural networks. Useful Tools and Resources for learning about Neuromorphic Computing.
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Tools and Resources for Neuromorphic Computing
Useful Tools and Resources for learning about Neuromorphic Computing. Neuromorphic computing models the way the brain works through spiking neural networks and other types of neural networks.
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Tools and Resource for Neuromorphic Computing
UsefuleTools and Resource for about Neuromorphic Computing.
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Cool Neuromorphic Computing Guide/Wiki
Neuromorphic Computing Guide/Wiki: https://github.com/mikeroyal/Neuromorphic-Computing-Guide
snntorch
Posts with mentions or reviews of snntorch.
We have used some of these posts to build our list of alternatives
and similar projects.
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Bio inspired computer vision
Spiking Neural Networks (SNNs): neural networks that use spiking neurons (i.e. neurons that communicate using asynchronous binary spikes similarly to biological neurons) instead of artificial neurons. Apart from this particularity, SNNs can be organized in any kind of topology we all know, like CNNs, ViT, etc. There are tons of approaches to train SNNs, like bio-inspired learning rules (STDP, three factor rules, etc) or adaptations of backprop (which remains the SOTA in a lot of vision tasks). A good resource to begin with backprop-trained SNNs: https://snntorch.readthedocs.io/en/latest/ .
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How to train brain-inspired spiking neural networks using lessons from deep learning. Interactive Colab notebook links in thread.
Github: https://github.com/jeshraghian/snntorch
What are some alternatives?
When comparing Neuromorphic-Computing-Guide and snntorch you can also consider the following projects:
norse - Deep learning with spiking neural networks (SNNs) in PyTorch.
spikingjelly - SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN) based on PyTorch.
lava - A Software Framework for Neuromorphic Computing
Spiking-Neural-Network - Pure python implementation of SNN
bindsnet - Simulation of spiking neural networks (SNNs) using PyTorch.
spaCy - đź’« Industrial-strength Natural Language Processing (NLP) in Python
pytorch-forecasting - Time series forecasting with PyTorch
NIPY - Workflows and interfaces for neuroimaging packages
TorchGA - Train PyTorch Models using the Genetic Algorithm with PyGAD
Shallow-learning - Replicating brain's low energy high efficiency model architecture & calculating (maths)
Kilosort - Fast spike sorting with drift correction for up to a thousand channels
Neuromorphic-Computing-Guide vs norse
snntorch vs spikingjelly
Neuromorphic-Computing-Guide vs lava
snntorch vs norse
Neuromorphic-Computing-Guide vs Spiking-Neural-Network
snntorch vs bindsnet
Neuromorphic-Computing-Guide vs spaCy
snntorch vs pytorch-forecasting
Neuromorphic-Computing-Guide vs NIPY
snntorch vs TorchGA
Neuromorphic-Computing-Guide vs Shallow-learning
snntorch vs Kilosort