francoispierrepaty / SubspaceRobustWassersteinLinks
Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"
☆29Updated 6 years ago
Alternatives and similar repositories for SubspaceRobustWasserstein
Users that are interested in SubspaceRobustWasserstein are comparing it to the libraries listed below
Sorting:
- Stochastic algorithms for computing Regularized Optimal Transport☆57Updated 6 years ago
- Code for Sliced Gromov-Wasserstein☆68Updated 5 years ago
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆27Updated 5 years ago
- ☆41Updated 5 years ago
- Code for our ICLR19 paper "Wasserstein Barycenters for Model Ensembling", Pierre Dognin, Igor Melnyk, Youssef Mroueh, Jarret Ross, Cicero…☆22Updated 5 years ago
- ☆12Updated 6 years ago
- Python implementation of smooth optimal transport.☆59Updated 4 years ago
- Sinkhorn Barycenters via Frank-Wolfe algorithm☆26Updated 5 years ago
- [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).☆56Updated 3 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Mixed-curvature Variational Autoencoders (ICLR 2020)☆64Updated 4 years ago
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆45Updated 2 years ago
- ☆38Updated 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
- Implementation of the Sliced Wasserstein Autoencoder using PyTorch☆103Updated 6 years ago
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆36Updated 5 years ago
- Learning generative models with Sinkhorn Loss☆30Updated 6 years ago
- The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).☆35Updated 4 years ago
- Graph matching and clustering by comparing heat kernels via optimal transport.☆27Updated 2 years ago
- Keras implementation of Deep Wasserstein Embeddings☆48Updated 7 years ago
- ☆30Updated 4 years ago
- Sliced Wasserstein Distance for Learning Gaussian Mixture Models☆65Updated 2 years ago
- NeurIPS 2021, Code for Measuring Generalization with Optimal Transport☆28Updated 3 years ago
- Learning the optimal transport map via input convex neural neworks☆42Updated 5 years ago
- PyTorch implementation of "Wasserstein-2 Generative Networks" (ICLR 2021)☆53Updated 2 years ago
- PyTorch implementation of the paper "Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization" (ICLR 2021)☆23Updated 3 years ago
- Code for "Variational Autoencoder with Learned Latent Structure"☆34Updated 4 years ago
- Code for "Learning with minibatch Wasserstein: asymptotic and gradient properties".☆13Updated 4 years ago
- Sliced Wasserstein Generator☆23Updated 6 years ago
- Morgan A. Schmitz., Matthieu Heitz, Nicolas Bonneel, Fred Ngole, David Coeurjolly, Marco Cuturi, Gabriel Peyré, and Jean-Luc Starck. "Was…☆20Updated 5 years ago