A collection of AWESOME things about domian adaptation

POT : Python Optimal Transport

TorchCFM: a Conditional Flow Matching library

An easy-to-use Python library for processing and manipulating 3D point clouds and meshes.

Optimal transport tools implemented with the JAX framework, to solve large scale matching problems of any flavor.

Approximating Wasserstein distances with PyTorch

[NeurIPS 2024] GaussianCube: A Structured and Explicit Radiance Representation for 3D Generative Modeling

FoldFlow: SE(3)-Stochastic Flow Matching for Protein Backbone Generation

PyTorch implementation of "Neural Optimal Transport" (ICLR 2023 Spotlight)

PyTorch for Quantitative Finance : Payoffs are Activations

[ICLR2023] PLOT: Prompt Learning with Optimal Transport for Vision-Language Models

Multi-omic single-cell optimal transport tools

A software package for analyzing snapshots of developmental processes

Neural Architecture Search with Bayesian Optimisation and Optimal Transport

Morphological Prototyping for Unsupervised Slide Representation Learning in Computational Pathology - CVPR 2024

Play, learn, solve, and analyze No-Limit Texas Hold Em. Implementation follows from Monte Carlo counter-factual regret minimization over with hierarchical K-means imperfect recall abstractions.

TorchDR - PyTorch Dimensionality Reduction

CVPR 2020, Semantic Correspondence as an Optimal Transport Problem, Pytorch Implementation.

Implementation of the Sliced Wasserstein Autoencoder using PyTorch

Optimal transport algorithms for Julia