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:
- Code for 'Memory-based dual Gaussian processes for sequential learning' (ICML 2023)☆12Updated 2 years ago
- Pytorch implementation of "Entropic Neural Optimal Transport via Diffusion Processes" (NeurIPS 2023, oral).☆39Updated 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…☆230Updated 4 years ago
- Repository for the paper "Riemannian Laplace approximations for Bayesian neural networks"☆11Updated last year
- ☆17Updated 3 years ago
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆38Updated 3 years ago
- Mutual information estimators and benchmark☆53Updated last month
- PyTorch implementation of the paper "Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization" (ICLR 2021)☆24Updated 3 years ago
- ☆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
- ☆32Updated 3 years ago
- A Python implementation of Monge optimal transportation☆49Updated 2 years ago
- Neural Diffusion Processes☆81Updated last year
- The Wasserstein Distance and Optimal Transport Map of Gaussian Processes☆52Updated 5 years ago
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆45Updated 2 years ago
- Code for Diff-SCM paper☆98Updated 2 years ago
- Code for ICE-BeeM paper - NeurIPS 2020☆87Updated 4 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆75Updated 3 years ago
- ☆41Updated 5 years ago
- Official implementation of "Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks", NeurIPS 2021.☆32Updated 7 months ago
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆78Updated 3 years ago
- Code for "Function Space Particle Optimization for Bayesian Neural Networks"☆18Updated 3 years ago
- Python notebooks for Optimal Transport between Gaussian Mixture Models☆46Updated 4 years ago
- Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)☆33Updated 4 years ago
- ☆20Updated 3 years ago
- The essence of my research, distilled for reusability. Enjoy 🥃!☆71Updated last year
- Code for Sliced Gromov-Wasserstein☆69Updated 5 years ago
- PyTorch implementation of "Wasserstein-2 Generative Networks" (ICLR 2021)☆57Updated 2 years ago
- Code for the paper "Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification" (2020)☆43Updated last year
- A Pytorch implementation of missing data imputation using optimal transport.☆104Updated 4 years ago