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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
DCGAN and WGAN implementation on Keras for Bird Generation
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
Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"
Code for the article "Learning to solve inverse problems using Wasserstein loss"
Tensorflow Implementation of Stochastic Wasserstein Autoencoder for Probabilistic Sentence Generation (NAACL 2019).
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.
Sparse simplex projection-based Wasserstein k-means
Python package for the ICML 2022 paper "Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors".
Improving word mover’s distance by leveraging self-attention matrix (Published in EMNLP 2023 Findings)
Variational Optimal Transportation
Julia interface for the Python Optimal Transport (POT) library
Code for our TMLR '24 Journal: MMD-Regularized UOT.
TensorFlow implementation of Wasserstein GAN (WGAN) with MNIST dataset.
Employing Optimal Transport metrics for Point Cloud Registration
Code for "Fixed Support Tree-Sliced Wasserstein Barycenter"
Implementation and results from "Beyond GOTEX: Using Multiple Feature Detectors for Better Texture Synthesis"
Optimal transport for comparing short brain connectivity between individuals | Optimal transport | Wasserstein distance | Barycenter | K-medoids | Isomap| Sulcus | Brain
Demonstration of Wasserstein GAN. Using Earth Mover's distance to measure similarity between two distributions
Wasserstein barycenter research for images