POT : Python Optimal Transport
-
Updated
Nov 29, 2024 - Python
POT : Python Optimal Transport
Optimal transport tools implemented with the JAX framework, to get differentiable, parallel and jit-able computations.
Official PyTorch implementation of the ICCV 2023 paper: From Chaos Comes Order: Ordering Event Representations for Object Recognition and Detection.
Improving word mover’s distance by leveraging self-attention matrix
Add a description, image, and links to the gromov-wasserstein topic page so that developers can more easily learn about it.
To associate your repository with the gromov-wasserstein topic, visit your repo's landing page and select "manage topics."