We introduce Devito, a new domain-specific language for implementing high-performance
finite-difference partial differential equation solvers. The motivating application is exploration …

We consider variants of trust-region and adaptive cubic regularization methods for non-
convex optimization, in which the Hessian matrix is approximated. Under certain condition …

While first-order optimization methods, such as SGD are popular in machine learning (ML),
they come with well-known deficiencies, including relatively-slow convergence, sensitivity to …

Conventional multi‐source waveform inversion using an objective function based on the
least‐square misfit cannot be applied to marine streamer acquisition data because of …

Ultrasound computed tomography (USCT) holds great promise for improving the detection
and management of breast cancer. Because they are based on the acoustic wave equation …

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 …

Ultrasound tomography (UST) scanners allow quantitative images of the human breast's
acoustic properties to be derived with potential applications in screening, diagnosis and …

This article is concerned with Monte Carlo methods for the estimation of the trace of an
implicitly given matrix AA whose information is only available through matrix-vector products …

Many seismic exploration techniques rely on the collection of massive data volumes that are
mined for information during processing. This approach has been extremely successful, but …

Seismic imaging is a linearized inversion problem relying on the minimization of a least‐
squares misfit functional as a function of the medium perturbation. The success of this …