4 papers · 1 filter
The Illusion of Fit: Spatially Resolved Assessment of Constitutive Model Validity in Elastography and Physics-Based Inverse Problems
Vincent C. Scholz, P. S. Koutsourelakis
Inferring the mechanical properties of soft tissues from measured deformations is a fundamental challenge in elastography. A rarely examined assumption underlying existing approach…
GenPANIS: A Latent-Variable Generative Framework for Forward and Inverse PDE Problems in Multiphase Media
Matthaios Chatzopoulos, Phaedon-Stelios Koutsourelakis
Inverse problems and inverse design in multiphase media, i.e., recovering or engineering microstructures to achieve target macroscopic responses, require operating on discrete-valu…
Weak neural variational inference for solving Bayesian inverse problems without forward models: applications in elastography
Vincent C. Scholz, Yaohua Zang, Phaedon-Stelios Koutsourelakis
In this paper, we introduce a novel, data-driven approach for solving high-dimensional Bayesian inverse problems based on partial differential equations (PDEs), called Weak Neural…
Physics-Aware Neural Implicit Solvers for multiscale, parametric PDEs with applications in heterogeneous media
Matthaios Chatzopoulos, Phaedon-Stelios Koutsourelakis
We propose Physics-Aware Neural Implicit Solvers (PANIS), a novel, data-driven framework for learning surrogates for parametrized Partial Differential Equations (PDEs). It consists…