judelo / gmmot
Python notebooks for Optimal Transport between Gaussian Mixture Models
☆42Updated 3 years ago
Alternatives and similar repositories for gmmot:
Users that are interested in gmmot are comparing it to the libraries listed below
- The Wasserstein Distance and Optimal Transport Map of Gaussian Processes☆52Updated 4 years ago
- Sliced Wasserstein Distance for Learning Gaussian Mixture Models☆62Updated last year
- PyTorch implementation of "Wasserstein-2 Generative Networks" (ICLR 2021)☆52Updated 2 years ago
- Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"☆28Updated 5 years ago
- L. Chizat, G. Peyré, B. Schmitzer, F-X. Vialard. Scaling Algorithms for Unbalanced Transport Problems. Preprint Arxiv:1607.05816, 2016.☆42Updated 8 years ago
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆44Updated 2 years ago
- ☆32Updated 2 years ago
- PyTorch implementation of the OT-Flow approach in arXiv:2006.00104☆51Updated 8 months ago
- Code for http://proceedings.mlr.press/v80/dvurechensky18a.html☆16Updated 6 years ago
- A set of tests for evaluating large-scale algorithms for Wasserstein-2 transport maps computation (NeurIPS 2021)☆39Updated 2 years ago
- [AISTATS2020] The official repository of "Invertible Generative Modling using Linear Rational Splines (LRS)".☆20Updated last year
- ☆39Updated 5 years ago
- MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.☆55Updated 5 years ago
- Gaussian Process Prior Variational Autoencoder☆83Updated 6 years ago
- Sinkhorn Barycenters via Frank-Wolfe algorithm☆24Updated 5 years ago
- Contains the code relative to the paper Partial Gromov-Wasserstein with Applications on Positive-Unlabeled Learning https://arxiv.org/abs…☆21Updated 5 years ago
- Code for Sliced Gromov-Wasserstein☆67Updated 5 years ago
- Code for ECML/PKDD paper: "LSMI-Sinkhorn: Semi-supervised Mutual Information Estimation with Optimal Transport"☆16Updated 3 years ago
- It is a repo which allows to compute all divergences derived from the theory of entropically regularized, unbalanced optimal transport. I…☆28Updated 2 years ago
- Learning the optimal transport map via input convex neural neworks☆41Updated 4 years ago
- CO-Optimal Transport☆42Updated 4 years ago
- Stochastic algorithms for computing Regularized Optimal Transport☆57Updated 6 years ago
- Generative Modeling with Optimal Transport Maps - ICLR 2022☆59Updated 2 years ago
- Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight☆52Updated 3 years ago
- ☆12Updated 8 months ago
- PyTorch implementation of Stein Variational Gradient Descent☆43Updated last year
- Backpropagation-Friendly-Eigendecomposition☆72Updated 5 years ago
- Gabriel Peyré, Marco Cuturi, Justin Solomon, Gromov-Wasserstein Averaging of Kernel and Distance Matrices, Proc. of ICML 2016.☆73Updated 8 years ago
- Optimal transport transforms☆22Updated 6 years ago
- ☆16Updated 3 years ago