The University of Texas Data Science and Machine Learning Lab

The University of Texas Data Science and Machine Learning Lab's repositories

MSW

The implementation of the Markovian sliced Wasserstein distances

Language:Python500

HSW

Hierarchical Sliced Wasserstein distance is a metric between probability measures that utilizes Hierarchical Radon Transform to projected measures to their one-dimensional projections.

Language:PythonMIT700

Mini-batch-OT

A new mini-batch framework for optimal transport in deep generative models, deep domain adaptation, approximate Bayesian computation, color transfer, and gradient flow.

Language:PythonMIT3600

CSW

A novel variant of sliced Wasserstein based on a new slicing technique that utilizes the convolution operator.

Language:PythonMIT1100

AmortizedSW

A framework using amortized optimization for seeking informative directions for sliced Wasserstein generative models.

Language:PythonMIT1100

transformer-mgk

This is the public github for our paper "Transformer with a Mixture of Gaussian Keys"

CC0-1.0200