marc-h-lambert / W-VILinks
The companion code for the paper "Variational inference via Wasserstein gradient flows (W-VI) M. Lambert, S. Chewi, F. Bach, S. Bonnabel, P. Rigollet."
☆14Updated 2 years ago
Alternatives and similar repositories for W-VI
Users that are interested in W-VI are comparing it to the libraries listed below
Sorting:
- ☆33Updated 3 years ago
- Mutual information estimators and benchmark☆55Updated 2 months ago
- Neural Diffusion Processes☆80Updated last year
- Pytorch implementation of "Entropic Neural Optimal Transport via Diffusion Processes" (NeurIPS 2023, oral).☆39Updated last year
- Repository for the paper "Riemannian Laplace approximations for Bayesian neural networks"☆11Updated last year
- ☆24Updated 3 years ago
- Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with…☆58Updated 2 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆75Updated 3 years ago
- Code for Diff-SCM paper☆99Updated 2 years ago
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆39Updated 3 years ago
- Code for 'Memory-based dual Gaussian processes for sequential learning' (ICML 2023)☆12Updated 2 years ago
- Generative Modeling with Optimal Transport Maps - ICLR 2022☆61Updated 3 years ago
- Free-form flows are a generative model training a pair of neural networks via maximum likelihood☆49Updated 5 months ago
- ☆25Updated 2 years ago
- The Wasserstein Distance and Optimal Transport Map of Gaussian Processes☆52Updated 5 years ago
- This is the reference implementation of our NeurIPS 2023 paper "Add and Thin: Diffusion for Temporal Point Processes"☆19Updated last year
- A list of awesome papers and cool resources on optimal transport and its applications in general! As you will notice, this list is curren…☆232Updated 4 years ago
- ☆17Updated 3 years ago
- ☆20Updated 4 years ago
- ☆14Updated 2 years ago
- Official codebase for the paper "Provable concept learning for interpretable predictions using variational inference".☆14Updated 3 years ago
- Large-scale uncertainty benchmark in deep learning.☆65Updated 7 months ago
- L1-regularized least squares with PyTorch☆72Updated 2 years ago
- A python/pytorch package for invertible neural networks☆70Updated 2 years ago
- The repository for Hyperbolic Representation Learning for Computer Vision, ECCV 2022☆66Updated 3 years ago
- Code for "Causal autoregressive flows" - AISTATS, 2021☆45Updated 4 years ago
- Code for ICE-BeeM paper - NeurIPS 2020☆87Updated 4 years ago
- ☆30Updated 7 months ago
- On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification☆21Updated 3 years ago
- This repository contains code for applying Riemannian geometry in machine learning.☆78Updated 4 years ago