Distances and representations of persistence diagrams
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Updated
Aug 27, 2026 - Python
Distances and representations of persistence diagrams
PyTorch implementation of slicing adversarial network (SAN)
Color Transfer via Optimal Transport
Sliced Wasserstein Generator
Cycle consistency generative adversarial networks with Sliced Wasserstein distance
Implementation of Sliced Wasserstein distance, SW barycenters and application to K-means clustering.
D<ee>p Learning [dev library] [CMS-MLG-25-002]
Code for our OTML NeurIPS paper : 'On Combining Expert Demonstrations in Imitation Learning via Optimal Transport
An unofficial JAX implementation of "A Sliced Wasserstein Loss for Neural Texture Synthesis" (CVPR 2021).
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