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Awesome GitHub RepositoriesGraph Dictionary Learning
Learning representative atoms that capture both node attributes and connectivity for graph-structured data.
Distinct from Graph Learning: Focuses on dictionary learning for graphs specifically, rather than general graph analysis or node embeddings.
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Awesome Graph Dictionary Learning GitHub Repositories
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- pythonot/pot
PythonOT/POT
2,751Auf GitHub ansehenPOT is an optimal transport library providing a collection of solvers for computing Wasserstein, Gromov-Wasserstein, and Fused Gromov-Wasserstein distances between probability distributions. It functions as a differentiable tensor framework that integrates with various tensor libraries to enable automatic differentiation and GPU acceleration. The project is distinguished by its ability to align data distributions across different metric spaces by comparing internal relational structures rather than coordinates. It implements mathematical optimization algorithms as differentiable layers, allow
Learns representative atoms for graph-structured data capturing both node attributes and connectivity.
Pythondomain-adaptationemdgromov-wasserstein
