POT : Python Optimal Transport

TorchCFM: a Conditional Flow Matching library

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

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

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

Neural Architecture Search with Bayesian Optimisation and Optimal Transport

TorchDR - PyTorch Dimensionality Reduction

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

Implementation of the Sliced Wasserstein Autoencoder using PyTorch

PyTorch implementation of slicing adversarial network (SAN)

Towards training VQ-VAE models robustly!

Official Implementation of AlignMixup - CVPR 2022

The code for "Point2Mask: Point-supervised Panoptic Segmentation via Optimal Transport", ICCV2023

Official PyTorch implementation of the ICCV 2023 paper: From Chaos Comes Order: Ordering Event Representations for Object Recognition and Detection.

Implementation of Motion Planning via Optimal Transport (MPOT) in PyTorch, NeurIPS 2023.

Sinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms. The SLA algorithm is described in full in this ICML 2021 paper: https://arxiv.org/abs/2102.08622.

Capsule research with our trivial contribution

ProGAN with Standard, WGAN, WGAN-GP, LSGAN, BEGAN, DRAGAN, Conditional GAN, InfoGAN, and Auxiliary Classifier GAN training methods