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Weak neural variational inference for solving Bayesian inverse problems
  without forward models: applications in elastography

Weak neural variational inference for solving Bayesian inverse problems without forward models: applications in elastography

30 July 2024
Vincent C. Scholz
Yaohua Zang
P. Koutsourelakis
ArXiv (abs)PDFHTML

Papers citing "Weak neural variational inference for solving Bayesian inverse problems without forward models: applications in elastography"

3 / 3 papers shown
Title
A unified physics-informed generative operator framework for general inverse problems
A unified physics-informed generative operator framework for general inverse problems
Gang Bao
Yaohua Zang
AI4CE
142
0
0
05 Nov 2025
Reinforcement Learning Closures for Underresolved Partial Differential Equations using Synthetic Data
Reinforcement Learning Closures for Underresolved Partial Differential Equations using Synthetic Data
Lothar Heimbach
Sebastian Kaltenbach
Petr Karnakov
Francis J. Alexander
Petros Koumoutsakos
AI4CE
332
1
0
16 May 2025
DGenNO: A Novel Physics-aware Neural Operator for Solving Forward and Inverse PDE Problems based on Deep, Generative Probabilistic Modeling
DGenNO: A Novel Physics-aware Neural Operator for Solving Forward and Inverse PDE Problems based on Deep, Generative Probabilistic ModelingJournal of Computational Physics (JCP), 2025
Yaohua Zang
P. Koutsourelakis
AI4CE
516
4
0
10 Feb 2025
1