Probabilistic numerical methods for PDE-constrained Bayesian inverse problems-Reference-Cited by-同舟云学术

Probabilistic numerical methods for PDE-constrained Bayesian inverse problems

Published:2017 Issue: Volume: Page:
ISSN:0094-243X
Container-title:AIP Conference Proceedings
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Author:

Cockayne Jon,Oates Chris,Sullivan Tim,Girolami Mark

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Author(s)

Link

http://aip.scitation.org/doi/pdf/10.1063/1.4985359

Reference11 articles.

1. Approximation of stochastic partial differential equations by a kernel-based collocation method

2. Jon Cockayne, Chris Oates, Tim Sullivan, and Mark Girolami. Probabilistic Meshless Methods for Partial Differential Equations and Bayesian Inverse Problems. arXiv:1605.07811v1, May 2016.

3. Patrick R Conrad, Mark Girolami, Simo Särkkä, Andrew Stuart, and Konstantinos Zygalakis. Statistical analysis of differential equations: introducing probability measures on numerical solutions. Statistics and Computing, 2016.

4. Deflation Techniques for Finding Distinct Solutions of Nonlinear Partial Differential Equations

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