JasonAltschuler / OptimalTransportNIPS17Links
Code for NIPS 2017 spotlight paper: "Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration" by Jason Altschuler, Jonathan Weed, and Philippe Rigollet. Full paper available at: https://papers.nips.cc/paper/6792-near-linear-time-approximation-algorithms-for-optimal-transport-via-sinkhorn-iteration.
☆31Updated 7 years ago
Alternatives and similar repositories for OptimalTransportNIPS17
Users that are interested in OptimalTransportNIPS17 are comparing it to the libraries listed below
Sorting:
- Implementation of Inexact Proximal point method for Optimal Transport☆49Updated 4 years ago
- Code for http://proceedings.mlr.press/v80/dvurechensky18a.html☆17Updated 7 years ago
- Python implementation of smooth optimal transport.☆60Updated 4 years ago
- demo codes for several approximate optimal transport solvers☆20Updated 7 years ago
- Stochastic algorithms for computing Regularized Optimal Transport☆58Updated 7 years ago
- Contains the code relative to the paper Partial Gromov-Wasserstein with Applications on Positive-Unlabeled Learning https://arxiv.org/abs…☆20Updated 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
- Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"☆29Updated 6 years ago
- Gabriel Peyré, Marco Cuturi, Justin Solomon, Gromov-Wasserstein Averaging of Kernel and Distance Matrices, Proc. of ICML 2016.☆74Updated 9 years ago
- Code for Sliced Gromov-Wasserstein☆69Updated 5 years ago
- Sliced Wasserstein Distance for Learning Gaussian Mixture Models☆66Updated 2 years ago
- A Python implementation of Monge optimal transportation☆49Updated last year
- Efficient Wasserstein Barycenter in MATLAB (for "Fast Discrete Distribution Clustering Using Wasserstein Barycenter with Sparse Support" …☆24Updated 6 years ago
- A collection of adaptive sparse multi-scale solvers for optimal transport and related optimization problems.☆53Updated 3 years ago
- MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.☆56Updated 6 years ago
- LEARNING LATENT PERMUTATIONS WITH GUMBEL-SINKHORN NETWORKS IMPLEMENTATION WITH PYTORCH☆79Updated 2 years ago
- Backpropagation-Friendly-Eigendecomposition☆73Updated 5 years ago
- Implementation of the Sliced Wasserstein Autoencoder using PyTorch☆103Updated 6 years ago
- The code for Differentiable Linearized ADMM (ICML 2019)☆36Updated 5 years ago
- Tensorflow Implementation of "Large-scale Optimal Transport and Mapping Estimation"(ICLR2018/NIPS 2017 OTML)☆20Updated 7 years ago
- tensorflow implementation of the Wasserstein (aka optimal transport) distance☆72Updated 4 years ago
- Optimal transport and generalizations