judelo / gmmotLinks
Python notebooks for Optimal Transport between Gaussian Mixture Models
☆46Updated 4 years ago
Alternatives and similar repositories for gmmot
Users that are interested in gmmot are comparing it to the libraries listed below
Sorting:
- The Wasserstein Distance and Optimal Transport Map of Gaussian Processes☆52Updated 4 years ago
- PyTorch implementation of "Wasserstein-2 Generative Networks" (ICLR 2021)☆53Updated 2 years ago
- Learning the optimal transport map via input convex neural neworks☆41Updated 5 years ago
- Generative Modeling with Optimal Transport Maps - ICLR 2022☆59Updated 3 years ago
- A set of tests for evaluating large-scale algorithms for Wasserstein-2 transport maps computation (NeurIPS 2021)☆41Updated 3 years ago
- MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.☆56Updated 6 years ago
- PyTorch implementation of the OT-Flow approach in arXiv:2006.00104☆53Updated 11 months ago
- Code for http://proceedings.mlr.press/v80/dvurechensky18a.html☆16Updated 6 years ago
- Gaussian Process Prior Variational Autoencoder☆84Updated 6 years ago
- Sliced Wasserstein Distance for Learning Gaussian Mixture Models☆62Updated 2 years ago
- A simple pytorch implementation of Langevin Monte Carlo algorithms.☆51Updated 5 years ago
- [AISTATS2020] The official repository of "Invertible Generative Modling using Linear Rational Splines (LRS)".☆20Updated 2 years ago
- ☆12Updated 11 months ago
- Sinkhorn Barycenters via Frank-Wolfe algorithm☆25Updated 5 years ago
- Convex potential flows☆83Updated 3 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- Stochastic algorithms for computing Regularized Optimal Transport☆57Updated 6 years ago
- Code for random Fourier features based on Rahimi and Recht's 2007 paper.☆55Updated 4 years ago
- ☆17Updated 3 years ago
- ☆72Updated 2 years ago
- PyTorch implementation of Stein Variational Gradient Descent☆45Updated 2 years ago
- A Python implementation of Monge optimal transportation☆49Updated last year
- Experiments for Neural Flows paper☆97Updated 3 years ago
- The companion code for the paper "Variational inference via Wasserstein gradient flows (W-VI) M. Lambert, S. Chewi, F. Bach, S. Bonnabel…☆14Updated 2 years ago
- [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)☆119Updated last year
- Gabriel Peyré, Marco Cuturi, Justin Solomon, Gromov-Wasserstein Averaging of Kernel and Distance Matrices, Proc. of ICML 2016.☆73Updated 8 years ago
- Python implementation of smooth optimal transport.☆58Updated 4 years ago
- ☆32Updated 2 years ago
- Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"☆28Updated 6 years ago
- Simple Importance Weighted Autoencoders (IWAE) implementation in Pytorch☆13Updated last week