bunnech / gwgan
Learning Generative Models across Incomparable Spaces (ICML 2019)
☆27Updated 4 years ago
Alternatives and similar repositories for gwgan:
Users that are interested in gwgan are comparing it to the libraries listed below
- Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"☆28Updated 5 years ago
- Learning Autoencoders with Relational Regularization☆45Updated 4 years ago
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆43Updated last year
- Code for Sliced Gromov-Wasserstein☆66Updated 5 years ago
- Stochastic algorithms for computing Regularized Optimal Transport☆57Updated 6 years ago
- ☆37Updated 4 years ago
- Contains the code relative to the paper Partial Gromov-Wasserstein with Applications on Positive-Unlabeled Learning https://arxiv.org/abs…☆21Updated 4 years ago
- Learning generative models with Sinkhorn Loss☆28Updated 6 years ago
- ☆39Updated 4 years ago
- Python implementation of smooth optimal transport.☆57Updated 3 years ago
- code submission to NeurIPS2019☆13Updated last year
- ☆12Updated 6 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
- ☆31Updated 4 years ago
- ☆53Updated 6 months ago
- Sinkhorn Barycenters via Frank-Wolfe algorithm☆24Updated 4 years ago
- [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).☆54Updated 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
- Mixed-curvature Variational Autoencoders (ICLR 2020)☆60Updated 3 years ago
- Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"☆49Updated 4 years ago
- The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).☆31Updated 4 years ago
- ☆24Updated 3 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Code for "Learning with minibatch Wasserstein: asymptotic and gradient properties".☆13Updated 3 years ago
- Sliced Wasserstein Generator☆23Updated 6 years ago
- Featurized Density Ratio Estimation☆20Updated 3 years ago
- Implementation of "Learning latent subspaces in variational autoencoders"☆20Updated 5 years ago
- Scaled MMD GAN☆36Updated 5 years ago
- Code for "Variational Autoencoder with Learned Latent Structure"☆33Updated 3 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆53Updated 3 months ago