Artificial intelligence has recently experienced remarkable advances, fueled by large
models, vast datasets, accelerated hardware, and, last but not least, the transformative …

We consider the problem of nonsmooth convex optimization with linear equality constraints,
where the objective function is only accessible through its proximal operator. This problem …

Constructing an analysis-suitable parameterization for the computational domain from its
boundary representation plays a crucial role in the isogeometric design-through-analysis …

This paper considers the effect of Anderson acceleration (AA) on the convergence order of
nonlinear solvers in fixed point form xk+ 1= g (xk), that are looking for a fixed point x∗ of g …

Anderson acceleration is a well-established and simple technique for speeding up fixed-
point computations with countless applications. This work introduces novel methods for …

Anderson acceleration (AA) is widely used for accelerating the convergence of nonlinear
fixed-point methods, but little is known about how to quantify the asymptotic convergence …

This work introduces, analyzes, and demonstrates an efficient and theoretically sound
filtering strategy to ensure the condition of the least-squares problem solved at each iteration …

This book on solvers for nonlinear equations is a user-oriented guide to algorithms and
implementation. It is a sequel to [111], which used MATLAB for the solvers and examples …

This paper considers improving the Picard and Newton iterative solvers for the Navier–
Stokes equations in the setting where data measurements or solution observations are …

Flow in variably saturated porous media is typically modeled by the Richards equation, a
nonlinear elliptic-parabolic equation which is notoriously challenging to solve numerically. In …