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In this paper, we propose a way to solve partial differential equations (PDEs) by combining machine learning techniques and the finite element method called Phi-FEM. For that, we use the Fourier Neural Operator (FNO), a learning mapping…

Numerical Analysis · Mathematics 2025-03-05 Michel Duprez , Vanessa Lleras , Alexei Lozinski , Vincent Vigon , Killian Vuillemot

The paper studies a method for solving elliptic partial differential equations posed on hypersurfaces in $\mathbb{R}^N$, $N=2,3$. The method builds upon the formulation introduced in Bertalmio et al., J. Comput. Phys., 174 (2001),…

Numerical Analysis · Mathematics 2013-04-08 Alexey Y. Chernyshenko , Maxim A. Olshanskii

Second-order partial differential equations in non-divergence form are considered. Equations of this kind typically arise as subproblems for the solution of Hamilton-Jacobi-Bellman equations in the context of stochastic optimal control, or…

Numerical Analysis · Mathematics 2020-08-13 Jan Blechschmidt , Roland Herzog , Max Winkler

We introduce a simple, rigorous, and unified framework for solving nonlinear partial differential equations (PDEs), and for solving inverse problems (IPs) involving the identification of parameters in PDEs, using the framework of Gaussian…

Numerical Analysis · Mathematics 2021-08-12 Yifan Chen , Bamdad Hosseini , Houman Owhadi , Andrew M Stuart

An important ingredient of any moving-mesh method for fluid-structure interaction (FSI) problems is the mesh deformation technique (MDT) used to adapt the computational mesh in the moving fluid domain. An ideal technique is computationally…

Computational Engineering, Finance, and Science · Computer Science 2020-06-26 Alexander Shamanskiy , Bernd Simeon

A multiscale numerical method is proposed for the solution of semi-linear elliptic stochastic partial differential equations with localized uncertainties and non-linearities, the uncertainties being modeled by a set of random parameters. It…

Numerical Analysis · Mathematics 2019-01-23 Anthony Nouy , Florent Pled

The forward-backward splitting method (FBS) for minimizing a nonsmooth composite function can be interpreted as a (variable-metric) gradient method over a continuously differentiable function which we call forward-backward envelope (FBE).…

Optimization and Control · Mathematics 2019-11-11 Lorenzo Stella , Andreas Themelis , Panagiotis Patrinos

In this paper, a highly parallel and derivative-free martingale neural network learning method is proposed to solve Hamilton-Jacobi-Bellman (HJB) equations arising from stochastic optimal control problems (SOCPs), as well as general…

Optimization and Control · Mathematics 2024-12-23 Wei Cai , Shuixin Fang , Wenzhong Zhang , Tao Zhou

We study iterative finite element approximations for the numerical approximation of semilinear elliptic boundary value problems with monotone nonlinear reactions of subcritical growth. The focus of our contribution is on an optimal a priori…

Numerical Analysis · Mathematics 2025-08-18 Florian Spicher , Thomas P. Wihler

We consider a large-scale quadratic eigenvalue problem (QEP), formulated using P1 finite elements on a fine scale reference mesh. This model describes damped vibrations in a structural mechanical system. In particular we focus on problems…

Numerical Analysis · Mathematics 2015-10-21 Axel Målqvist , Daniel Peterseim

We consider a sketched implementation of the finite element method for elliptic partial differential equations on high-dimensional models. Motivated by applications in real-time simulation and prediction we propose an algorithm that…

Numerical Analysis · Mathematics 2020-04-22 Robert Lung , Yue Wu , Dimitris Kamilis , Nick Polydorides

We introduce an inertial quasi-Newton Forward-Backward Splitting Algorithm to solve a class of monotone inclusion problems. While the inertial step is computationally cheap, in general, the bottleneck is the evaluation of the resolvent…

Optimization and Control · Mathematics 2024-03-18 Shida Wang , Jalal Fadili , Peter Ochs

We introduce some new proximal quasi-Newton methods for unconstrained multiobjective optimization problems (in short, UMOP), where each objective function is the sum of a twice continuously differentiable strongly convex function and a…

Optimization and Control · Mathematics 2022-04-08 Jian-Wen Peng , Jie Ren

We analyze a sequential quadratic programming algorithm for solving a class of abstract optimization problems. Assuming that the initial point is in an $L^2$ neighborhood of a local solution that satisfies no-gap second-order sufficient…

Optimization and Control · Mathematics 2026-05-19 Eduardo Casas , Mariano Mateos

A semidefinite program (SDP) is a particular kind of convex optimization problem with applications in operations research, combinatorial optimization, quantum information science, and beyond. In this work, we propose variational quantum…

Quantum Physics · Physics 2024-06-19 Dhrumil Patel , Patrick J. Coles , Mark M. Wilde

In this paper we derive and analyse efficient and stable numerical methods for accurate numerical simulations of nonlinear dynamic shear ruptures on non-planar faults embedded in 3D elastic solids using dual-paring (DP) summation by parts…

Numerical Analysis · Mathematics 2022-07-19 Kenneth Duru , Christopher Williams , Frederick Fung

The LP-Newton method solves the linear programming problem (LP) by repeatedly projecting a current point onto a certain relevant polytope. In this paper, we extend the algorithmic framework of the LP-Newton method to the second-order cone…

Optimization and Control · Mathematics 2021-05-31 Takayuki Okuno , Mirai Tanaka

We propose a new nonconforming \(P_1\) finite element method for elliptic interface problems. The method is constructed on a locally anisotropic mixed mesh, which is generated by fitting the interface through a simple connection of…

Numerical Analysis · Mathematics 2025-10-08 Chenchen Geng , Hua Wang , Qichen Zhang

This article considers the extension of two-grid $hp$-version discontinuous Galerkin finite element methods for the numerical approximation of second-order quasilinear elliptic boundary value problems of monotone type to the case when…

Numerical Analysis · Mathematics 2021-12-10 Scott Congreve , Paul Houston

We develop polynomial-time heuristic methods to solve unimodular quadratic programs (UQPs) approximately, which are known to be NP-hard. In the UQP framework, we maximize a quadratic function of a vector of complex variables with unit…

Optimization and Control · Mathematics 2017-03-28 Shankarachary Ragi , Edwin K. P. Chong , Hans D. Mittelmann
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