Wasserstein barycenter research for images
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Updated
Oct 13, 2018 - Python
Wasserstein barycenter research for images
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
MXNet/Gluon implementation of Wasserstein Auto-Encoders (WAE)
Code for our TMLR '24 Journal: MMD-Regularized UOT.
Demonstration of Wasserstein GAN. Using Earth Mover's distance to measure similarity between two distributions
Employing Optimal Transport metrics for Point Cloud Registration
Code for "Fixed Support Tree-Sliced Wasserstein Barycenter"
Generating Atari Images with WGANs in PyTorch
TensorFlow implementation of Wasserstein GAN (WGAN) with MNIST dataset.
Julia interface for the Python Optimal Transport (POT) library
Variational Optimal Transportation
Pytorch Implementation for Topic Modeling with Wasserstein Autoencoders
Improving word mover’s distance by leveraging self-attention matrix
Python package for the ICML 2022 paper "Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors".
Optimal Transport and Optimization related experiments.
Sparse simplex projection-based Wasserstein k-means
Source code for "Training Generative Adversarial Networks Via Turing Test".
code for "Determining Gains Acquired from Word Embedding Quantitatively Using Discrete Distribution Clustering" ACL 2017
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