A tutorial on Gaussian process regression: modelling, exploring, and exploiting functions

DOI10.1016/j.jmp.2018.03.001zbMath1416.62648OpenAlexW2804446681WikidataQ61888664 ScholiaQ61888664MaRDI QIDQ1735988

Eric Schulz, Andreas Krause, Maarten Speekenbrink

Publication date: 29 March 2019

Published in: Journal of Mathematical Psychology (Search for Journal in Brave)

Full work available at URL: https://discovery.ucl.ac.uk/id/eprint/10050029/

zbMATH Keywords

active learningbandit problemsGaussian process regressionexploration-exploitation

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Gaussian processes (60G15) Applications of statistics to psychology (62P15)

Related Items (14)

Modelling human active search in optimizing black-box functions ⋮ Parameter sensitivity for wave-breaking closures in Boussinesq-type models ⋮ Efficient hybrid Bayesian optimization algorithm with adaptive expected improvement acquisition function ⋮ Derivative-based SINDy (DSINDy): addressing the challenge of discovering governing equations from noisy data ⋮ Multielement polynomial chaos kriging-based metamodelling for Bayesian inference of non-smooth systems ⋮ A non-intrusive solution to the ill-conditioning problem of the gradient-enhanced Gaussian covariance matrix for Gaussian processes ⋮ Physics-informed information field theory for modeling physical systems with uncertainty quantification ⋮ Discovery of PDEs driven by data with sharp gradient or discontinuity ⋮ Multiscale Modeling of Metal-Ceramic Spatially Tailored Materials via Gaussian Process Regression and Peridynamics ⋮ Dual order-reduced Gaussian process emulators (DORGP) for quantifying high-dimensional uncertain crack growth using limited and noisy data ⋮ Are Humans Bayesian in the Optimization of Black-Box Functions? ⋮ Relevance vector machine with tuning based on self-adaptive differential evolution approach for predictive modelling of a chemical process ⋮ Developing automated valuation models for estimating property values: a comparison of global and locally weighted approaches ⋮ Cylinder drag minimization through wall actuation: a Bayesian optimization approach

Uses Software

• tgp
• SFO
• GPstuff
• GPML
• GPy
• TensorFlow
• GPflow
• GitHub
• Mousetrap
• MouseTracker
• SafeOpt

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• A tutorial on Bayesian nonparametric models
• Bayesian parameter estimation in the Expectancy Valence model of the Iowa gambling task
• A tutorial on adaptive design optimization
• A tutorial on kernel methods for categorization
• Bayesian Treed Gaussian Process Models With an Application to Computer Modeling
• The Multi-Armed Bandit Problem: Decomposition and Computation
• Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting
• Probabilistic numerics and uncertainty in computations
• An Explicit Representation of a Stationary Gaussian Process
• A new look at the statistical model identification

This page was built for publication: A tutorial on Gaussian process regression: modelling, exploring, and exploiting functions