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Author:
Santiago Maniches
Summary:
Topology-aware machine learning toolkit for persistent-homology features, differentiable topology losses, simplicial and Hodge operators, signal analysis, and reproducible evaluation.
Latest version:
0.0.9
Required dependencies:
networkx
|
numpy
|
pyyaml
|
ripser
|
scikit-learn
|
scipy
Optional dependencies:
gudhi
|
hypothesis
|
mypy
|
numpy
|
pytest
|
pytest-benchmark
|
pytest-cov
|
ruff
|
toponetx
|
torch
|
torch-geometric
|
torch-topological
|
torchvision
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