A collection of AWESOME things about domian adaptation
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Updated
May 15, 2024
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.
Optimal transport tools implemented with the JAX framework, to get differentiable, parallel and jit-able computations.
Approximating Wasserstein distances with PyTorch
TorchCFM: a Conditional Flow Matching library
A software package for analyzing snapshots of developmental processes
Neural Architecture Search with Bayesian Optimisation and Optimal Transport
Implementation of the Sliced Wasserstein Autoencoders
PyTorch implementation of "Neural Optimal Transport" (ICLR 2023 Spotlight)
Implementation of the Sliced Wasserstein Autoencoder using PyTorch
An implementation of Wasserstein Fair Classification, a conference paper submitted to UAI 2019.
Solve large instance of semi-discrete optimal transport problems and other Monge-Ampere equations
Python interface for a 2D optimal transport / Monge Ampère solver using Laguerre diagrams
CVPR 2020, Semantic Correspondence as an Optimal Transport Problem, Pytorch Implementation.
A PyTorch implementation of adaptive Monte Carlo Optimal Transport algorithm
Dynamic Time Warping (DTW) and related algorithms in Julia, at Julia speeds
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。
The Wasserstein Distance and Optimal Transport Map of Gaussian Processes
Curated materials for different machine learning related summer schools
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