146 citations · 240 across the 6 of their papers we have counts for
6 papers
Amortized Normalizing Flows for Transcranial Ultrasound with Uncertainty Quantification
Rafael Orozco, Mathias Louboutin, Ali Siahkoohi +3
We present a novel approach to transcranial ultrasound computed tomography that utilizes normalizing flows to improve the speed of imaging and provide Bayesian uncertainty quantifi…
CoShaRP: A Convex Program for Single-shot Tomographic Shape Sensing
Ajinkya Kadu, Tristan van Leeuwen, K. Joost Batenburg
We introduce single-shot X-ray tomography that aims to estimate the target image from a single cone-beam projection measurement. This linear inverse problem is extremely under-dete…
Total-variation regularization strategies in full-waveform inversion
Ernie Esser, Lluis Guasch, Tristan van Leeuwen +2
We propose an extended full-waveform inversion formulation that includes general convex constraints on the model. Though the full problem is highly nonconvex, the overarching optim…
A penalty method for PDE-constrained optimization in inverse problems
Tristan van Leeuwen, Felix J. Herrmann
Many inverse and parameter estimation problems can be written as PDE-constrained optimization problems. The goal, then, is to infer the parameters, typically coefficients of the PD…
Sparse seismic imaging using variable projection
Aleksandr Y. Aravkin, Tristan van Leeuwen, Ning Tu
We consider an important class of signal processing problems where the signal of interest is known to be sparse, and can be recovered from data given auxiliary information about ho…
Robust inversion via semistochastic dimensionality reduction
Aleksandr Aravkin, Michael P. Friedlander, Tristan van Leeuwen
We consider a class of inverse problems where it is possible to aggregate the results of multiple experiments. This class includes problems where the forward model is the solution…