3 citations · 4 across the 3 of their papers we have counts for
6 papers
Learn an index operator by CNN for solving diffusive optical tomography: a deep direct sampling method
Jiahua Jiang, Yi Li, Ruchi Guo
In this work, we investigate the diffusive optical tomography (DOT) problem in the case that limited boundary measurements are available. Motivated by the direct sampling method (D…
Low-CP-rank Tensor Completion via Practical Regularization
Jiahua Jiang, Fatoumata Sanogo, Carmeliza Navasca
Dimension reduction techniques are often used when the high-dimensional tensor has relatively low intrinsic rank compared to the ambient dimension of the tensor. The CANDECOMP/PARA…
Construct Deep Neural Networks Based on Direct Sampling Methods for Solving Electrical Impedance Tomography
Ruchi Guo, Jiahua Jiang
This work investigates the electrical impedance tomography (EIT) problem when only limited boundary measurements are available, which is known to be challenging due to the extreme…
Hybrid Projection Methods with Recycling for Inverse Problems
Julianne Chung, Eric de Sturler, Jiahua Jiang
Iterative hybrid projection methods have proven to be very effective for solving large linear inverse problems due to their inherent regularizing properties as well as the added fl…
Hybrid Projection Methods for Large-scale Inverse Problems with Mixed Gaussian Priors
Taewon Cho, Julianne Chung, Jiahua Jiang
When solving ill-posed inverse problems, a good choice of the prior is critical for the computation of a reasonable solution. A common approach is to include a Gaussian prior, whic…
Adaptive greedy algorithms based on parameter-domain decomposition and reconstruction for the reduced basis method
Jiahua Jiang, Yanlai Chen
The reduced basis method (RBM) empowers repeated and rapid evaluation of parametrized partial differential equations through an offline-online decomposition, a.k.a. a learning-exec…