cagrell / gp_constrLinks
Python model for constrained GP
☆26Updated 4 years ago
Alternatives and similar repositories for gp_constr
Users that are interested in gp_constr are comparing it to the libraries listed below
Sorting:
- A Python package to learn the Koopman operator.☆61Updated this week
- Code for efficiently sampling functions from GP(flow) posteriors☆73Updated 4 years ago
- Exploring how to to deal with uncertain inputs with gaussian process regression models.☆27Updated 4 years ago
- Multi-Output Gaussian Process Toolkit☆176Updated 4 months ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated 11 months ago
- This repository contains the code for the paper "Geometry-aware Bayesian Optimization in Roboticsusing Riemannian Matérn Kernels" (CoRL'2…☆21Updated 2 years ago
- neural networks to learn Koopman eigenfunctions☆430Updated last year
- ☆30Updated 7 months ago
- Offline Contextual Bayesian Optimization☆14Updated 2 years ago
- ☆28Updated 2 years ago
- Stochastic variational heteroscedastic Gaussian process☆15Updated 6 years ago
- A package for computing data-driven approximations to the Koopman operator.☆378Updated 11 months ago
- Bayesian neural networks via MCMC: tutorial☆58Updated 11 months ago
- GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data☆49Updated 4 years ago
- Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"☆30Updated last year
- ☆193Updated 6 months ago
- A general-purpose Python package for Koopman theory using deep learning.☆108Updated 2 weeks ago
- Nonparametric Differential Equation Modeling☆54Updated last year
- Bayesian Neural Network Surrogates for Bayesian Optimization☆61Updated last year
- Streaming sparse Gaussian process approximations☆68Updated 3 years ago
- A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch☆115Updated last week
- A Bayesian optimization toolbox built on TensorFlow☆240Updated this week
- Flexible and efficient tools for high-dimensional approximation, scientific machine learning and uncertainty quantification.☆65Updated last week
- ☆370Updated 3 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆43Updated last year
- Heterogeneous Multi-output Gaussian Processes☆53Updated 5 years ago
- SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics☆153Updated 4 years ago
- Methods for numerical differentiation of noisy data in python☆123Updated this week
- Gaussian processes in JAX and Flax.☆539Updated last week
- Learning Neural Differential Algebraic Equations via Operator Splitting☆19Updated 2 months ago