Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations | Paper Citation Record

Observation a4a159c6-5d7d-405b-b30a-57de2d305b9e · outbound

This paper cites Babuška, F.

Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Babuška, F

Reference 1

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This paper cites Batlle, Y.

Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Batlle, Y

Reference 3

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This paper cites Benning and M.

Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Benning and M

Reference 4

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This paper cites Berner, P.

Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Berner, P

Reference 5

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

Reference 7

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Reference 8

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Reference 9

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Reference 10

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Reference 11

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This paper cites Cuomo, V.

Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Cuomo, V

Reference 12

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This paper cites Daxberger*, A.

Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Daxberger*, A

Reference 13

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Reference 14

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This paper cites De Ryck, S.

Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations De Ryck, S

Reference 15

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This paper cites De Ryck and S.

Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations De Ryck and S

Reference 16

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This paper cites A deep surrogate approach to efficient Bayesian inversion in PDE and integral equation models.

Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations A deep surrogate approach to efficient Bayesian inversion in PDE and integral equation models

Reference 17

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This paper cites A hierarchical multilevel Markov chain Monte Carlo algorithm with applications to uncertainty quantification in subsurface flow.

Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations A hierarchical multilevel Markov chain Monte Carlo algorithm with applications to uncertainty quantification in subsurface flow

Reference 18

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

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This paper cites Efendiev, T.

Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Efendiev, T

Reference 20

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

Reference 21

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Reference 22

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Reference 23

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This paper cites Goodfellow, Y.

Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Goodfellow, Y

Reference 24

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This paper cites Gribonval, G.

Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Gribonval, G

Reference 25

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

Reference 26

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

Reference 27

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This paper cites Helin, A.

Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Helin, A

Reference 28

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This paper cites Hennig, M.

Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Hennig, M

Reference 29

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Reference 30

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This paper cites Hochreiter and J.

Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Hochreiter and J

Reference 31

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Hornik, M

Reference 32

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Immer, M

Reference 33

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Jacot, F

Reference 34

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Kaipio and E

Reference 36

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Kaipio and E

Reference 37

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Kaltenbacher, A

Reference 38

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Adam: A Method for Stochastic Optimization

Reference 40

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Kovachki, Z

Reference 41

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Kristiadi, M

Reference 43

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Marzouk and D

Reference 51

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Matérn.Spatial variation, volume 36 ofLecture Notes in Statistics

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Metropolis, A

Reference 55

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Mishra and R

Reference 56

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Rahaman, A

Reference 58

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Raissi, P

Reference 59

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Raissi, P

Reference 60

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Sacks, W

Reference 65

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Schwab and J

Reference 66

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Sharma, S

Reference 67

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

Reference 68

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Sirignano and K

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Tancik, P

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations V oulodimos, N

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations An Expert's Guide to Training Physics-informed Neural Networks

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Wendland.Scattered data approximation, volume 17 ofCambridge Monographs on Applied and Computational Mathematics

Reference 82

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations The Case for Bayesian Deep Learning

Reference 83

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Unresolved cited work

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Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations Xiu and G

Reference 85

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