pmorenoz / ModularGPLinks
Modular Gaussian Processes
☆16Updated 3 years ago
Alternatives and similar repositories for ModularGP
Users that are interested in ModularGP are comparing it to the libraries listed below
Sorting:
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 7 years ago
- A library implementing the kernels for and experiments using extrinsic gauge equivariant vector field Gaussian Processes☆25Updated 4 years ago
- Library for Bayesian Quadrature☆32Updated 6 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆74Updated 5 years ago
- Python and MATLAB code for Stein Variational sampling methods☆26Updated 6 years ago
- Kernel Identification Through Transformers☆14Updated 2 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- Minimal Gaussian process library in JAX with a simple (custom) approach to state management.☆12Updated last year
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
- Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling☆36Updated 4 years ago
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆29Updated 10 months ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆25Updated 5 years ago
- Efficient non-linear PCA through kernel PCA with the Nyström method☆13Updated 2 years ago
- ☆37Updated 5 years ago
- ☆52Updated 2 years ago
- Refining continuous-in-depth neural networks☆42Updated 4 years ago
- A repository with implementations of major papers on Gaussian Process regression models, implemented from scratch in Python, notably incl…☆14Updated 3 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆88Updated 3 years ago
- A lightweight didactic library of kernel methods using the back-end JAX.☆12Updated 2 years ago
- Nonparametric Differential Equation Modeling☆56Updated last year
- orbital MCMC☆10Updated 4 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆45Updated 7 years ago
- Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods☆22Updated 2 years ago
- ☆15Updated 3 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- ☆10Updated 3 years ago
- Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'☆47Updated 4 years ago
- Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features☆24Updated 6 years ago
- Implementation of Action Matching for the Schrödinger equation☆25Updated 2 years ago
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆10Updated 3 years ago