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A deep surrogate approach to efficient Bayesian inversion in PDE and
  integral equation models
v1v2v3v4 (latest)

A deep surrogate approach to efficient Bayesian inversion in PDE and integral equation models

3 October 2019
Teo Deveney
Amelia Gosse
Peter Du
ArXiv (abs)PDFHTML

Papers citing "A deep surrogate approach to efficient Bayesian inversion in PDE and integral equation models"

4 / 4 papers shown
Deep surrogate accelerated delayed-acceptance HMC for Bayesian inference
  of spatio-temporal heat fluxes in rotating disc systems
Deep surrogate accelerated delayed-acceptance HMC for Bayesian inference of spatio-temporal heat fluxes in rotating disc systems
Teo Deveney
E. Mueller
T. Shardlow
AI4CE
186
0
0
05 Apr 2022
An overview on deep learning-based approximation methods for partial
  differential equations
An overview on deep learning-based approximation methods for partial differential equations
C. Beck
Martin Hutzenthaler
Arnulf Jentzen
Benno Kuckuck
692
175
0
22 Dec 2020
Adaptive Physics-Informed Neural Networks for Markov-Chain Monte Carlo
Adaptive Physics-Informed Neural Networks for Markov-Chain Monte Carlo
M. A. Nabian
Hadi Meidani
252
8
0
03 Aug 2020
Bayesian differential programming for robust systems identification
  under uncertainty
Bayesian differential programming for robust systems identification under uncertaintyProceedings of the Royal Society A (Proc. R. Soc. A), 2020
Jianlong Wu
Mohamed Aziz Bhouri
P. Perdikaris
OOD
368
38
0
15 Apr 2020
1
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