pytorch-topological
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aidos-lab
A topological machine learning framework based on PyTorch
Just covering the basics for new users: suppose you don't care about topology _at all_, what's the smallest thing you can add to your code to make it 'topology-aware?'
- Some previous benchmarks by @crisbodnar: https://colab.research.google.com/drive/1CbLnKu4v964Gxb2FDsxp1kgPwe0pOKpl?usp=sharing - Suggestion for integration: use `str` parameter for `VietorisRipsComplex` - Add as optional dependency
Currently, the implementation of TOGL ignores the following features: - handling higher-order information properly - expanding simplicial complexes - making use of the dimension of features
Hi, I feel like there should be in-built functions for visualizing Persistence diagrams. Like now, I am using matplotlib, to scatter plot the `diagram` of `PersistenceInformation`, but it requires extra...
Import PersLayer to PyTorch topological. As apart of this effort, it would be nice to include the following deliverables: - PyTorch layer - Unit tests - Example of usage -...
Currently, there are no examples present for usage of TOGL. Would be good to provide example of use case.
As stated in the roadmap, currently, `guddhi` and `giotto-ph` are used for various purposes. We want to be able to allow the user to specify which backend to use, and...