A spectrum of physics-informed Gaussian processes for regression in
engineering

A spectrum of physics-informed Gaussian processes for regression in engineering

19 September 2023

D. J. Pitchforth

Matthew R. Jones

Papers citing "A spectrum of physics-informed Gaussian processes for regression in engineering"

16 / 16 papers shown

Title
Constraining Gaussian processes for physics-informed acoustic emission mapping Matthew R. Jones T. Rogers E. Cross AI4CE 62 16 0 03 Jun 2022
AutoIP: A United Framework to Integrate Physics into Gaussian Processes D. Long Ziyi Wang Aditi S. Krishnapriyan Robert M. Kirby Shandian Zhe Michael W. Mahoney AI4CE 77 15 0 24 Feb 2022
Learning Nonparametric Volterra Kernels with Gaussian Processes M. Ross M. Smith Mauricio A. Alvarez GP 26 7 0 10 Jun 2021
Grey-box models for wave loading prediction D. J. Pitchforth T. Rogers U. T. Tygesen E. Cross 31 32 0 10 May 2021
Probabilistic Inference for Structural Health Monitoring: New Modes of Learning from Data L. Bull P. Gardner T. Rogers E. Cross N. Dervilis Keith Worden 17 21 0 02 Mar 2021
A Bayesian methodology for localising acoustic emission sources in complex structures M. R. Jones T. Rogers Keith Worden E. Cross 31 48 0 21 Dec 2020
A Survey of Constrained Gaussian Process Regression: Approaches and Implementation Challenges L. Swiler Mamikon A. Gulian A. Frankel Cosmin Safta J. Jakeman GP AI4CE 62 106 0 16 Jun 2020
Gaussian Process Manifold Interpolation for Probabilistic Atrial Activation Maps and Uncertain Conduction Velocity Sam Coveney C. Corrado C. Roney D. O'Hare Steven E. Williams M. OÑeill Steven Niederer R. Clayton J. Oakley Richard D. Wilkinson 28 41 0 22 Apr 2020
Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features Arno Solin Manon Kok 35 23 0 10 Apr 2019
A Gaussian process latent force model for joint input-state estimation in linear structural systems R. Nayek S. Chakraborty S. Narasimhan 25 91 0 29 Mar 2019
Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems Laura von Rueden S. Mayer Katharina Beckh B. Georgiev Sven Giesselbach ... Rajkumar Ramamurthy Michal Walczak Jochen Garcke Christian Bauckhage Jannis Schuecker 62 638 0 29 Mar 2019
Spectral Mixture Kernels for Multi-Output Gaussian Processes Gabriel Parra Felipe A. Tobar 38 78 0 05 Sep 2017
Hidden Physics Models: Machine Learning of Nonlinear Partial Differential Equations M. Raissi George Karniadakis AI4CE PINN 70 1,137 0 02 Aug 2017
Bayesian Probabilistic Numerical Methods Jon Cockayne Chris J. Oates T. Sullivan Mark Girolami 64 166 0 13 Feb 2017
Modeling and interpolation of the ambient magnetic field by Gaussian processes Arno Solin Manon Kok Niklas Wahlström Thomas B. Schon Simo Särkkä 29 119 0 15 Sep 2015
Gaussian Process Kernels for Pattern Discovery and Extrapolation A. Wilson Ryan P. Adams GP 66 607 0 18 Feb 2013