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POT: Python Optimal Transport, has the following main features: * A large set of differentiable solvers for optimal transport problems, including: * Exact linear OT, entropic and quadratic regularized OT, * Gromov-Wasserstein (GW) distances, Fused GW distances and variants of quadratic OT, * Unbalanced and partial OT for different divergences, * OT barycenters (Wasserstein and GW) for fixed and free support, * Fast OT solvers in 1D, on the circle and between Gaussian Mixture Models (GMMs), * Many ML related solvers, such as domain adaptation, optimal transport mapping estimation, subspace learning, Graph Neural Networks (GNNs) layers. * Several backends for easy use with Pytorch, Jax, Tensorflow, Numpy and Cupy arrays.
| Package | Summary | Distribution | Download |
| python313-pot-0.9.6.post1-1.2.i586.html | Python Optimal Transport Library | OpenSuSE Ports Tumbleweed for i586 | python313-pot-0.9.6.post1-1.2.i586.rpm |
| python313-pot-0.9.6.post1-1.2.x86_64.html | Python Optimal Transport Library | OpenSuSE Tumbleweed for x86_64 | python313-pot-0.9.6.post1-1.2.x86_64.rpm |
| python313-pot-0.9.6.post1-1.1.riscv64.html | Python Optimal Transport Library | OpenSuSE Ports Tumbleweed for riscv64 | python313-pot-0.9.6.post1-1.1.riscv64.rpm |
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