12 citations · 13 across the 4 of their papers we have counts for
5 papers
Data selection: at the interface of PDE-based inverse problem and randomized linear algebra
Kathrin Hellmuth, Ruhui Jin, Qin Li +1
All inverse problems rely on data to recover unknown parameters, yet not all data are equally informative. This raises the central question of data selection. A distinctive challen…
Continuous nonlinear adaptive experimental design with gradient flow
Ruhui Jin, Qin Li, Stephen O. Mussmann +1
In computational inverse problems, the optimal experimental design (OED) problem seeks the best locations in time and space at which to take measurements. We investigate the nonlin…
Unique reconstruction for discretized inverse problems: a random sketching approach via subsampling
Ruhui Jin, Qin Li, Anjali Nair +1
Theoretical inverse problems are often studied in an ideal infinite-dimensional setting. The well-posedness theory provides a unique reconstruction of the parameter function, when…
Optimal design for linear models via gradient flow
Ruhui Jin, Martin Guerra, Qin Li +1
Optimal experimental design (OED) aims to choose the observations in an experiment to be as informative as possible, according to certain statistical criteria. In the linear case (…
SUNLayer: Stable denoising with generative networks
Ruhui Jin, Dustin G. Mixon, Soledad Villar
Deep neural networks are often used to implement powerful generative models for real-world data. Notable applications include image denoising, as well as other classical inverse pr…