marc-h-lambert / W-VI
The companion code for the paper "Variational inference via Wasserstein gradient flows (W-VI) M. Lambert, S. Chewi, F. Bach, S. Bonnabel, P. Rigollet."
☆10Updated last year
Alternatives and similar repositories for W-VI:
Users that are interested in W-VI are comparing it to the libraries listed below
- Repository for the paper "Riemannian Laplace approximations for Bayesian neural networks"☆10Updated last year
- Implementation of the paper "Neural Wasserstein Gradient Flows for Discrepancies with Riesz Kernels"☆11Updated 10 months ago
- Pytorch implementation of "Entropic Neural Optimal Transport via Diffusion Processes" (NeurIPS 2023, oral).☆35Updated 10 months ago
- Code for 'Memory-based dual Gaussian processes for sequential learning' (ICML 2023)☆12Updated last year
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆31Updated 2 years ago
- Official Implementation of the paper: "A Rate-Distorion View of Uncertainty Quantification", ICML 2024☆28Updated 4 months ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 5 years ago
- Lightweight MCMC sampling for PyTorch Models aka My Corona Project☆44Updated 4 years ago
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆97Updated 9 months ago
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆43Updated last year
- Official code for the ICLR 2021 paper Neural ODE Processes☆70Updated 2 years ago
- PyTorch implementation of the paper "Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization" (ICLR 2021)☆23Updated 2 years ago
- A set of tests for evaluating large-scale algorithms for Wasserstein-2 transport maps computation (NeurIPS 2021)☆38Updated 2 years ago
- Official repo for Trumpets: Injective Flows for Inference and Inverse Problems☆13Updated 3 years ago
- ☆22Updated last year
- Deep universal probabilistic programming with Python and PyTorch☆11Updated 4 years ago
- Learning the optimal transport map via input convex neural neworks☆40Updated 4 years ago
- NeurIPS'23: Energy Discrepancies: A Score-Independent Loss for Energy-Based Models☆14Updated 3 months ago
- All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)☆21Updated 2 years ago
- Kernel Stein Discrepancy Descent : a method to sample from unnormalized densities☆21Updated 9 months ago
- Density Ratio Estimation via Infinitesimal Classification (AISTATS 2022 Oral)☆17Updated 2 years ago
- Implementation of Action Matching☆38Updated last year
- Code for ICE-BeeM paper - NeurIPS 2020☆86Updated 3 years ago
- ☆22Updated 2 years ago
- GP Sinkhorn Implementation, paper: https://www.mdpi.com/1099-4300/23/9/1134☆22Updated 2 years ago
- Simple (and cheap!) neural network uncertainty estimation☆60Updated this week
- ☆47Updated last week
- ☆39Updated 4 years ago
- PyTorch linear operators for curvature matrices (Hessian, Fisher/GGN, KFAC, ...)☆25Updated 2 weeks ago
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆9Updated 2 years ago