Probabilistic Gradients for Fast Calibration of Differential Equation Models-Reference-Cited by-同舟云学术

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Probabilistic Gradients for Fast Calibration of Differential Equation Models

Published:2021-01 Issue:4 Volume:9 Page:1643-1672
ISSN:2166-2525
Container-title:SIAM/ASA Journal on Uncertainty Quantification
language:en
Short-container-title:SIAM/ASA J. Uncertainty Quantification

Author:

Cockayne Jonathan,Duncan Andrew

Funder

Lloyds Register Program on Data Centric Engineering

Alan Turing Institute

Engineering and Physical Sciences Research Council

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Subject

Applied Mathematics,Discrete Mathematics and Combinatorics,Statistics, Probability and Uncertainty,Modeling and Simulation,Statistics and Probability

Link

https://epubs.siam.org/doi/pdf/10.1137/20M1364424

Reference38 articles.

1. Kernels for Vector-Valued Functions: A Review

2. Emulation and Sensitivity Analysis of the Community Multiscale Air Quality Model for a UK Ozone Pollution Episode

3. A Survey of Projection-Based Model Reduction Methods for Parametric Dynamical Systems

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Theoretical Guarantees for the Statistical Finite Element Method;SIAM/ASA Journal on Uncertainty Quantification;2023-11-30

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