Jiacheng-Zhu-AIML / WGPOTLinks
The Wasserstein Distance and Optimal Transport Map of Gaussian Processes
☆52Updated 5 years ago
Alternatives and similar repositories for WGPOT
Users that are interested in WGPOT are comparing it to the libraries listed below
Sorting:
- Python notebooks for Optimal Transport between Gaussian Mixture Models☆47Updated 4 years ago
- ☆13Updated 2 years ago
- Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022☆45Updated 3 years ago
- Official Implementation of "Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions" (ICLR, …☆87Updated 2 years ago
- Official implementation of Transformer Neural Processes☆78Updated 3 years ago
- Functional Optimal Transport: Map Estimation and Domain Adaptation for Functional data☆27Updated 4 years ago
- Code to reproduce the experimental results from the paper "Active Invariant Causal Prediction: Experiment Selection Through Stability", b…☆21Updated 2 years ago
- Euclidean Wasserstein-2 optimal transportation☆47Updated 2 years ago
- Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"☆60Updated last year
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆78Updated 3 years ago
- beta-NLL introduced in our paper "On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks" ICLR 2022☆46Updated 3 years ago
- Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight☆55Updated 4 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Code repository of the paper "CITRIS: Causal Identifiability from Temporal Intervened Sequences" and "iCITRIS: Causal Representation Lear…☆56Updated 2 years ago
- Tutorial on amortized optimization for learning to optimize over continuous domains☆249Updated 2 months ago
- Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".☆37Updated 3 years ago
- Code for "Variational Autoencoder with Learned Latent Structure"☆34Updated 4 years ago
- Neural Diffusion Processes☆80Updated last year
- Train and visualise a latent variable model of moving objects.☆15Updated 5 years ago
- PyTorch implementation of the OT-Flow approach in arXiv:2006.00104☆57Updated last year
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆29Updated 10 months ago
- Experiments for Neural Flows paper☆100Updated 4 years ago
- [ICLR 2022] Path integral sampler☆52Updated 2 years ago
- PyTorch implementation of Stein Variational Gradient Descent☆47Updated 2 years ago
- Neural Laplace: Differentiable Laplace Reconstructions for modelling any time observation with O(1) complexity.☆81Updated 8 months ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆75Updated 3 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆90Updated 5 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆88Updated 3 years ago
- ☆105Updated 4 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago