vienmai / drotLinks
Douglas-Rachford Splitting for Optimal Transport
☆11Updated 4 years ago
Alternatives and similar repositories for drot
Users that are interested in drot are comparing it to the libraries listed below
Sorting:
- Fast hyperparameter settings for non-smooth estimators:☆40Updated 2 years ago
- Code for Deep Structured Mixtures of Gaussian Processes (DSMGPs)☆11Updated 3 years ago
- Learning the optimal transport map via input convex neural neworks☆41Updated 5 years ago
- A set of tests for evaluating large-scale algorithms for Wasserstein-2 transport maps computation (NeurIPS 2021)☆44Updated 3 years ago
- Algorithms for computations on random manifolds made easier☆93Updated last year
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆45Updated 2 years ago
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆29Updated 8 months ago
- Code for efficiently sampling functions from GP(flow) posteriors☆73Updated 4 years ago
- Source code for "Continuous Regularized Wasserstein Barycenters" [NeurIPS 2020].☆14Updated 4 years ago
- PEPit is a package enabling computer-assisted worst-case analyses of first-order optimization methods.☆88Updated last month
- Python notebooks for Optimal Transport between Gaussian Mixture Models☆46Updated 4 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆35Updated 3 years ago
- Differentiation through cone programs☆106Updated last month
- L. Chizat, G. Peyré, B. Schmitzer, F-X. Vialard. Scaling Algorithms for Unbalanced Transport Problems. Preprint Arxiv:1607.05816, 2016.☆42Updated 8 years ago
- This repository contains the source code to perform Geometry-aware Bayesian Optimization (GaBO) on Riemannian manifolds.☆53Updated 3 years ago
- Code for random Fourier features based on Rahimi and Recht's 2007 paper.☆57Updated 4 years ago
- ☆12Updated last year
- A general-purpose, deep learning-first library for constrained optimization in PyTorch☆142Updated 3 months ago
- Lightweight MCMC sampling for PyTorch Models aka My Corona Project☆49Updated last month
- This repository contains code for applying Riemannian geometry in machine learning.☆78Updated 4 years ago
- The Wasserstein Distance and Optimal Transport Map of Gaussian Processes☆53Updated 5 years ago
- Optimal transport and generalizations☆64Updated 6 years ago
- Nonparametric Differential Equation Modeling☆54Updated last year
- This repository contains the code for the paper "Geometry-aware Bayesian Optimization in Roboticsusing Riemannian Matérn Kernels" (CoRL'2…☆21Updated 2 years ago
- code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"☆100Updated 6 years ago
- Mutual information estimators and benchmark☆53Updated 3 weeks ago
- Deep universal probabilistic programming with Python and PyTorch☆12Updated 5 years ago
- Code for "Variational Autoencoder with Learned Latent Structure"☆34Updated 4 years ago
- ☆26Updated last week