PRML algorithms implemented in Python

Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)

A PyTorch library and evaluation platform for end-to-end compression research

disentanglement_lib is an open-source library for research on learning disentangled representations.

The Stan Math Library is a C++ template library for automatic differentiation of any order using forward, reverse, and mixed modes. It includes a range of built-in functions for probabilistic model…

PyTorch implementation and benchmark of Video Compression

A list of awesome papers and cool resources on optimal transport and its applications in general! As you will notice, this list is currently mostly focused on optimal transport for machine learning…

Some methods for comparing network representations in deep learning and neuroscience.

Visualize/test models for visual representation by synthesizing images.

Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding

Code for Sliced Gromov-Wasserstein

Data compression in JAX

Distributional Sliced-Wasserstein distance code

Add a cat to your webpage!

Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"

My implementation of John K. Kruschke's Doing Bayesian Data Analysis 2nd edition using Python and Numpyro.

Python implementation of IDVAE