pytorch-symbolic
Provides symbolic API for model creation in PyTorch. (by sjmikler)
lava-dl
Deep Learning library for Lava (by lava-nc)
pytorch-symbolic | lava-dl | |
---|---|---|
3 | 1 | |
57 | 138 | |
- | 3.6% | |
4.7 | 7.8 | |
about 1 year ago | 3 days ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | BSD 3-clause "New" or "Revised" 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.
pytorch-symbolic
Posts with mentions or reviews of pytorch-symbolic.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-11-14.
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Package for visualizing pytorch models
Question: will your library work with pytorch functional api ?
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Pytorch Symbolic: an equivalent of Keras Functional API
See on GitHub
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Functional API for PyTorch - easier and quicker way to create models
You should be able to create any acyclic network with this API, including multiple input/output ones. For more information go to github and if you face any problems, please leave an Issue there.
lava-dl
Posts with mentions or reviews of lava-dl.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-04-04.
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Has anyone used Spiking Neural Networks (SNNs) for image processing?
Surrogate gradient learning w/ backpropagation: for short, you can use backpropagation with SNNs (by a little trick during the backward pass). Super easy to implement, super efficient. You have a deep SNN trained via backprop with any type of input you want. Personally, that is completely my jam. Maybe you can use such paradigm to easily train an SNN in your biomed image dataset. Good repos: SnnTorch comes with the best tutorials to explain SNNs and surrogate gradient learning. This is the fastest way to understand the field and begin to implement you solution. Nevertheless, spikingjelly remains a better option when it comes to implement your ideas (better memory efficiency, etc). Good mention to lava-dl, with which you can train a neural network and directly transfer it into neuromorphic hardware (Intel Loihi) if you have access to this kind of chip.
What are some alternatives?
When comparing pytorch-symbolic and lava-dl you can also consider the following projects:
torchview - torchview: visualize pytorch models
spikingjelly - SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN) based on PyTorch.
rtdl-revisiting-models - (NeurIPS 2021) Revisiting Deep Learning Models for Tabular Data
learnopencv - Learn OpenCV : C++ and Python Examples
shap - A game theoretic approach to explain the output of any machine learning model.