POT : Python Optimal Transport
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Updated
Jul 2, 2024 - Python
POT : Python Optimal Transport
Code for our TMLR '24 Journal: MMD-Regularized UOT.
Improving word mover’s distance by leveraging self-attention matrix
Implementation and results from "Beyond GOTEX: Using Multiple Feature Detectors for Better Texture Synthesis"
A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.
A Python implementation of Monge optimal transportation
Tensorflow Implementation of Stochastic Wasserstein Autoencoder for Probabilistic Sentence Generation (NAACL 2019).
Python package for the ICML 2022 paper "Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors".
Optimal transport for comparing short brain connectivity between individuals | Optimal transport | Wasserstein distance | Barycenter | K-medoids | Isomap| Sulcus | Brain
Pytorch Implementation for Topic Modeling with Wasserstein Autoencoders
TensorFlow implementation of Wasserstein GAN (WGAN) with MNIST dataset.
The Wasserstein Distance and Optimal Transport Map of Gaussian Processes
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
Wasserstein barycenter research for images
GANs Implementations in Keras
DCGAN and WGAN implementation on Keras for Bird Generation
Code for the article "Learning to solve inverse problems using Wasserstein loss"
Demonstration of Wasserstein GAN. Using Earth Mover's distance to measure similarity between two distributions
Tensorflow implementation of Wasserstein GAN - arxiv: https://arxiv.org/abs/1701.07875
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