Shallow-learning
Replicating brain's low energy high efficiency model architecture & calculating (maths) (by sleepingcat4)
snntorch
Deep and online learning with spiking neural networks in Python (by jeshraghian)
Shallow-learning | snntorch | |
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1 | 2 | |
2 | 1,112 | |
- | - | |
2.4 | 9.2 | |
about 1 year ago | 12 days ago | |
Python | Python | |
Apache License 2.0 | 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.
Shallow-learning
Posts with mentions or reviews of Shallow-learning.
We have used some of these posts to build our list of alternatives
and similar projects.
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Shallow Deep Learning Models and Complexity Calculation - A TensorFlow Project Implementation
If you're interested in learning more about shallow deep learning models or just want to play around with some code, feel free to check out my project on GitHub: https://github.com/sleepingcat4/Shallow-learning. I'd love to hear your thoughts and feedback on the project, so feel free to comment or reach out to me directly.
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