A collection of AWESOME things about domian adaptation

POT : Python Optimal Transport

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

TorchCFM: a Conditional Flow Matching library

Optimal transport tools implemented with the JAX framework, to get differentiable, parallel and jit-able computations.

Approximating Wasserstein distances with PyTorch

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

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

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

PyTorch Library for Quantitative Finance

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

A software package for analyzing snapshots of developmental processes

Neural Architecture Search with Bayesian Optimisation and Optimal Transport

Multi-omic single-cell optimal transport tools

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

Implementation of the Sliced Wasserstein Autoencoder using PyTorch

Dynamic Time Warping (DTW) and related algorithms in Julia, at Julia speeds

Optimal transport algorithms for Julia

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

書籍『最適輸送の理論とアルゴリズム』のサポートページです。