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1605.07811
Cited By
Probabilistic Numerical Methods for Partial Differential Equations and Bayesian Inverse Problems
25 May 2016
Jon Cockayne
Chris J. Oates
T. Sullivan
Mark Girolami
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Papers citing
"Probabilistic Numerical Methods for Partial Differential Equations and Bayesian Inverse Problems"
15 / 15 papers shown
Title
The Inverse of Exact Renormalization Group Flows as Statistical Inference
D. Berman
Marc S. Klinger
24
15
0
21 Dec 2022
GaussED: A Probabilistic Programming Language for Sequential Experimental Design
Matthew A. Fisher
Onur Teymur
Chris J. Oates
40
1
0
15 Oct 2021
Bayesian Numerical Methods for Nonlinear Partial Differential Equations
Junyang Wang
Jon Cockayne
O. Chkrebtii
T. Sullivan
Chris J. Oates
59
19
0
22 Apr 2021
Probabilistic Numeric Convolutional Neural Networks
Marc Finzi
Roberto Bondesan
Max Welling
BDL
AI4TS
31
13
0
21 Oct 2020
A Role for Symmetry in the Bayesian Solution of Differential Equations
Junyang Wang
Jon Cockayne
Chris J. Oates
27
7
0
24 Jun 2019
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data
Yinhao Zhu
N. Zabaras
P. Koutsourelakis
P. Perdikaris
PINN
AI4CE
46
854
0
18 Jan 2019
A Modern Retrospective on Probabilistic Numerics
Chris J. Oates
T. Sullivan
AI4CE
24
64
0
14 Jan 2019
Adversarial Uncertainty Quantification in Physics-Informed Neural Networks
Yibo Yang
P. Perdikaris
AI4CE
PINN
32
355
0
09 Nov 2018
Probabilistic Linear Solvers: A Unifying View
Simon Bartels
Jon Cockayne
Ilse C. F. Ipsen
Philipp Hennig
17
24
0
08 Oct 2018
Neural network augmented inverse problems for PDEs
Jens Berg
K. Nystrom
22
41
0
27 Dec 2017
Bayesian Probabilistic Numerical Methods
Jon Cockayne
Chris J. Oates
T. Sullivan
Mark Girolami
21
164
0
13 Feb 2017
Probabilistic Numerical Methods for PDE-constrained Bayesian Inverse Problems
Jon Cockayne
Chris J. Oates
T. Sullivan
Mark Girolami
AI4CE
21
79
0
15 Jan 2017
Inferring solutions of differential equations using noisy multi-fidelity data
M. Raissi
P. Perdikaris
George Karniadakis
AI4CE
18
286
0
16 Jul 2016
Gamblets for opening the complexity-bottleneck of implicit schemes for hyperbolic and parabolic ODEs/PDEs with rough coefficients
H. Owhadi
Lei Zhang
AI4CE
23
69
0
24 Jun 2016
Mercer kernels and integrated variance experimental design: connections between Gaussian process regression and polynomial approximation
Alex A. Gorodetsky
Youssef M. Marzouk
36
38
0
27 Feb 2015
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