POT : Python Optimal Transport
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Updated
Nov 21, 2024 - Python
POT : Python Optimal Transport
Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN
Tensorflow implementation of Wasserstein GAN - arxiv: https://arxiv.org/abs/1701.07875
Optimal transport algorithms for Julia
Code for Supervised Word Mover's Distance (SWMD)
DCGAN and WGAN implementation on Keras for Bird Generation
Wasserstein Introspective Neural Networks (CVPR 2018 Oral)
The Wasserstein Distance and Optimal Transport Map of Gaussian Processes
A Python implementation of Monge optimal transportation
Torch implementation of Wasserstein GAN https://arxiv.org/abs/1701.07875
A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.
FML (Francis' Machine-Learnin' Library) - A collection of utilities for machine learning tasks
Tensorflow Implementation of Stochastic Wasserstein Autoencoder for Probabilistic Sentence Generation (NAACL 2019).
Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"
Code for the article "Learning to solve inverse problems using Wasserstein loss"
GANs Implementations in Keras
code for "Determining Gains Acquired from Word Embedding Quantitatively Using Discrete Distribution Clustering" ACL 2017
Source code for "Training Generative Adversarial Networks Via Turing Test".
Optimal Transport and Optimization related experiments.
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