Joshuaalbert / heterogpLinks
Provides a heteroscedastic noise latent for a sparse variational Gaussian process using GPflow
☆13Updated 5 years ago
Alternatives and similar repositories for heterogp
Users that are interested in heterogp are comparing it to the libraries listed below
Sorting:
- Scalable Gaussian Process Regression with Derivatives☆38Updated 6 years ago
- Nonparametric Differential Equation Modeling☆56Updated last year
- Learning unknown ODE models with Gaussian processes☆27Updated 7 years ago
- This repository contains the source code to perform Geometry-aware Bayesian Optimization (GaBO) on Riemannian manifolds.☆54Updated 4 years ago
- ☆28Updated 3 years ago
- Code repo for "Kernel Interpolation for Scalable Online Gaussian Processes"☆64Updated 4 years ago
- GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data☆48Updated 4 years ago
- Unifying sparse approximations for Gaussian process regression and classification, using Power EP☆22Updated 9 years ago
- ☆21Updated 3 years ago
- Data-driven dynamical systems toolbox.☆78Updated last month
- Streaming sparse Gaussian process approximations☆69Updated 3 years ago
- Code for Deep Structured Mixtures of Gaussian Processes (DSMGPs)☆11Updated 3 years ago
- This repository contains the code for the paper "Geometry-aware Bayesian Optimization in Roboticsusing Riemannian Matérn Kernels" (CoRL'2…☆21Updated 2 years ago
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆29Updated 10 months ago
- Batch and incremental Sparse Spectrum Gaussian Process for Regression☆10Updated 4 years ago
- By introducing a differentiable contact model, DiffCoSim extends the applicability of Lagrangian/Hamiltonian-inspired neural networks to …☆37Updated 2 years ago
- [ICML 2022] Learning Efficient and Robust Ordinary Differential \\ Equations via Invertible Neural Networks☆10Updated 2 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 efficiently sampling functions from GP(flow) posteriors☆74Updated 5 years ago
- Parametric Gaussian Process Regression for Big Data☆45Updated 5 years ago
- Reference implementation of Optimistic Expected Improvement.☆50Updated 5 years ago
- ☆16Updated 7 years ago
- Fully nonstationary, heteroscedastic GP for Matlab☆16Updated last year
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 7 years ago
- Exploring how to to deal with uncertain inputs with gaussian process regression models.☆27Updated 4 years ago
- ☆45Updated 2 years ago
- Stochastic variational heteroscedastic Gaussian process☆15Updated 6 years ago
- A library implementing the kernels for and experiments using extrinsic gauge equivariant vector field Gaussian Processes☆25Updated 4 years ago
- Infinite-horizon Gaussian processes☆33Updated 5 years ago
- Koopman Kernels for Learning Dynamical Systems from Trajectory Data☆31Updated 2 years ago