kimiandj / gswLinks
☆42Updated 5 years ago
Alternatives and similar repositories for gsw
Users that are interested in gsw are comparing it to the libraries listed below
Sorting:
- Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"☆29Updated 6 years ago
- Distributional Sliced-Wasserstein distance code☆50Updated last year
- Stochastic algorithms for computing Regularized Optimal Transport☆58Updated 7 years ago
- PyTorch implementation for the ICLR 2020 paper "Understanding the Limitations of Variational Mutual Information Estimators"☆77Updated 5 years ago
- Sliced Wasserstein Distance for Learning Gaussian Mixture Models☆66Updated 2 years ago
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆27Updated 5 years ago
- Sinkhorn Barycenters via Frank-Wolfe algorithm☆27Updated 5 years ago
- Code for Sliced Gromov-Wasserstein☆69Updated 6 years ago
- Implementation of the Sliced Wasserstein Autoencoder using PyTorch☆102Updated 7 years ago
- ☆14Updated 5 years ago
- PyTorch implementation of the OT-Flow approach in arXiv:2006.00104☆57Updated last year
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆78Updated 3 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Code for the paper "Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification" (2020)☆43Updated last year
- PyTorch implementation of "Wasserstein-2 Generative Networks" (ICLR 2021)☆57Updated 2 years ago
- ☆37Updated 5 years ago
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆45Updated 2 years ago
- NeurIPS 2021, Code for Measuring Generalization with Optimal Transport☆28Updated 4 years ago
- ☆149Updated 3 years ago
- Official implementation of "Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks", NeurIPS 2021.☆32Updated 8 months ago
- ☆59Updated 2 years ago
- Code implementation of paper: Deep Network Classification by Scattering and Homotopy Dictionary Learning☆25Updated 4 years ago
- ☆89Updated 4 years ago
- Learning generative models with Sinkhorn Loss☆30Updated 7 years ago
- This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).☆51Updated 4 years ago
- Code for ICE-BeeM paper - NeurIPS 2020☆87Updated 4 years ago
- Robust Optimal Transport code☆43Updated 3 years ago
- Code for "Variational Autoencoder with Learned Latent Structure"☆34Updated 4 years ago
- LEARNING LATENT PERMUTATIONS WITH GUMBEL-SINKHORN NETWORKS IMPLEMENTATION WITH PYTORCH☆81Updated 2 years ago
- Featurized Density Ratio Estimation☆20Updated 4 years ago