1 citations · 2 across the 9 of their papers we have counts for
4 papers · 1 filter
ROMNet: a hybrid reduced order modeling and machine learning approach to waveform inversion
Liliana Borcea, Alexander Mamonov, Kui Ren +2
Waveform inversion seeks to estimate the wave speed of a heterogeneous, inaccessible medium, from time-resolved measurements of the waves at user controlled sensors. We consider th…
Data Completion for Electrical Impedance Tomography by Conditional Diffusion Models
Ke Chen, Haizhao Yang, Chugang Yi
Data scarcity is a fundamental barrier in Electrical Impedance Tomography (EIT), as undersampled Dirichlet-to-Neumann (DtN) measurements can substantially degrade conductivity reco…
Error analysis for learning the time-stepping operator of evolutionary PDEs
Ke Chen, Meenakshi Krishnan, Haizhao Yang
Deep neural networks (DNNs) have recently emerged as effective tools for approximating solution operators of partial differential equations (PDEs) including evolutionary problems.…
Let data talk: data-regularized operator learning theory for inverse problems
Ke Chen, Chunmei Wang, Haizhao Yang
Regularization plays a pivotal role in integrating prior information into inverse problems. While many deep learning methods have been proposed to solve inverse problems, determini…