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Surrogates
Gaussian Process Modeling, Design, and Optimization for the Applied Sciences
Taschenbuch von Robert B. Gramacy

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Beschreibung

Surrogates is a graduate textbook, on topics at the interface between machine learning,spatial statistics,computer simulation,meta-modeling,design of experiments,and optimization. Experimentation through simulation,management of dynamic processes,online and real-time analysis,automation and practical application are at the forefront.

Surrogates is a graduate textbook, on topics at the interface between machine learning,spatial statistics,computer simulation,meta-modeling,design of experiments,and optimization. Experimentation through simulation,management of dynamic processes,online and real-time analysis,automation and practical application are at the forefront.

Über den Autor

Robert B. Gramacy is a professor of Statistics in the College of Science at Virginia Tech. Research interests include Bayesian modeling methodology, statistical computing, Monte Carlo inference, nonparametric regression, sequential design, and optimization under uncertainty. Bobby enjoys cycling and ice hockey, and watching his kids grow up too fast.

Inhaltsverzeichnis

1 Historical Perspective
2 Four Motivating Datasets
3 Steepest Ascent and Ridge Analysis
4 Space-filling Design
5 Gaussian process regression
6 Model-Based Design for GPs
7 Optimization
8 Calibration and Sensitivity
9 GP Fidelity and Scale
10 Heteroskedasticity
Appendix A Numerical Linear Algebra for Fast GPs
Appendix B An Experiment Game

Details
Erscheinungsjahr: 2021
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 560
ISBN-13: 9781032242552
ISBN-10: 1032242558
Einband: Kartoniert / Broschiert
Autor: Gramacy, Robert B.
Hersteller: Taylor & Francis Ltd
Maße: 177 x 253 x 33 mm
Von/Mit: Robert B. Gramacy
Erscheinungsdatum: 13.12.2021
Gewicht: 1,046 kg
preigu-id: 128249780
Über den Autor

Robert B. Gramacy is a professor of Statistics in the College of Science at Virginia Tech. Research interests include Bayesian modeling methodology, statistical computing, Monte Carlo inference, nonparametric regression, sequential design, and optimization under uncertainty. Bobby enjoys cycling and ice hockey, and watching his kids grow up too fast.

Inhaltsverzeichnis

1 Historical Perspective
2 Four Motivating Datasets
3 Steepest Ascent and Ridge Analysis
4 Space-filling Design
5 Gaussian process regression
6 Model-Based Design for GPs
7 Optimization
8 Calibration and Sensitivity
9 GP Fidelity and Scale
10 Heteroskedasticity
Appendix A Numerical Linear Algebra for Fast GPs
Appendix B An Experiment Game

Details
Erscheinungsjahr: 2021
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 560
ISBN-13: 9781032242552
ISBN-10: 1032242558
Einband: Kartoniert / Broschiert
Autor: Gramacy, Robert B.
Hersteller: Taylor & Francis Ltd
Maße: 177 x 253 x 33 mm
Von/Mit: Robert B. Gramacy
Erscheinungsdatum: 13.12.2021
Gewicht: 1,046 kg
preigu-id: 128249780
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