POT : Python Optimal Transport
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Updated
Jun 22, 2024 - Python
POT : Python Optimal Transport
Tensorflow implementation of Wasserstein GAN - arxiv: https://arxiv.org/abs/1701.07875
Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN
DCGAN and WGAN implementation on Keras for Bird Generation
Code for Supervised Word Mover's Distance (SWMD)
Wasserstein Introspective Neural Networks (CVPR 2018 Oral)
The Wasserstein Distance and Optimal Transport Map of Gaussian Processes
Code for the article "Learning to solve inverse problems using Wasserstein loss"
A Python implementation of Monge optimal transportation
A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.
Optimal transport algorithms for Julia
FML (Francis' Machine-Learnin' Library) - A collection of utilities for machine learning tasks
code for "Determining Gains Acquired from Word Embedding Quantitatively Using Discrete Distribution Clustering" ACL 2017
Tensorflow Implementation of Stochastic Wasserstein Autoencoder for Probabilistic Sentence Generation (NAACL 2019).
GANs Implementations in Keras
Torch implementation of Wasserstein GAN https://arxiv.org/abs/1701.07875
Variational Optimal Transportation
Optimal Transport and Optimization related experiments.
Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"
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