313 citations · 704 across the 32 of their papers we have counts for
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math.OC2024
An augmented Lagrangian trust-region method with inexact gradient evaluations to accelerate constrained optimization problems using model hyperreduction
Tianshu Wen, Matthew J. Zahr
We present an augmented Lagrangian trust-region method to efficiently solve constrained optimization problems governed by large-scale nonlinear systems with application to partial…
math.NA2024
Preconditioned iterative solvers for constrained high-order implicit shock tracking methods
Jakob Vandergrift, Matthew J. Zahr
High-order implicit shock tracking (fitting) is a class of high-order numerical methods that use numerical optimization to simultaneously compute a high-order approximation to a co…
math.NA2024★ 1 cited
Symmetric, Optimization-based, Cross-element Compatible Nodal Distributions for High-order Finite Elements
Julian M. Kaufmann, Matthew J. Zahr
We present a general framework to construct symmetric, well-conditioned, cross-element compatible nodal distributions that can be used for high-order and high-dimensional finite el…