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We extend the analysis and discretization of the Kirchhoff-Love plate bending problem from [T. F\"uhrer, N. Heuer, A.H. Niemi, An ultraweak formulation of the Kirchhoff-Love plate bending model and DPG approximation, arXiv:1805.07835, 2018]…

Numerical Analysis · Mathematics 2018-05-24 Thomas Führer , Norbert Heuer

In this paper, we investigate a sequentially decoupled numerical method for solving the fully coupled quasi-static thermo-poroelasticity problems with nonlinear convective transport. The symmetric interior penalty discontinuous Galerkin…

Numerical Analysis · Mathematics 2025-09-09 Fan Chen , Ming Cui , Chenguang Zhou

We study the optimal transport problem for $d>2$ discrete measures. This is a linear programming problem on $d$-tensors. It gives a way to compute a "distance" between two sets of discrete measures. We introduce an entropic regularization…

Computer Vision and Pattern Recognition · Computer Science 2021-07-27 Shmuel Friedland

We present a fully discrete finite element method for the interior null controllability problem subject to the wave equation. For the numerical scheme, piece-wise affine continuous elements in space and finite differences in time are…

Numerical Analysis · Mathematics 2023-05-10 Erik Burman , Ali Feizmohammadi , Lauri Oksanen

This article devises a new numerical method for first-order transport problems by using the primal-dual weak Galerkin (PD-WG) finite element method recently developed in scientific computing. The PD-WG method is based on a variational…

Numerical Analysis · Mathematics 2020-07-15 Chunmei Wang , Junping Wang

Hybrid High-Order methods for elliptic diffusion problems have been originally formulated for loads in the Lebesgue space $L^2(\Omega)$. In this paper we devise and analyze a variant thereof, which is defined for any load in the dual…

Numerical Analysis · Mathematics 2019-05-01 Alexandre Ern , Pietro Zanotti

In this work, we give a novel general approach for distribution testing. We describe two techniques: our first technique gives sample-optimal testers, while our second technique gives matching sample lower bounds. As a consequence, we…

Data Structures and Algorithms · Computer Science 2016-05-10 Ilias Diakonikolas , Daniel M. Kane

We consider a class of discrete optimization problems that aim to maximize a submodular objective function subject to a distributed partition matroid constraint. More precisely, we consider a networked scenario in which multiple agents…

Optimization and Control · Mathematics 2020-11-19 Alexander Robey , Arman Adibi , Brent Schlotfeldt , George J. Pappas , Hamed Hassani

We establish numerical methods for solving the martingale optimal transport problem (MOT) - a version of the classical optimal transport with an additional martingale constraint on transport's dynamics. We prove that the MOT value can be…

Probability · Mathematics 2019-04-08 Gaoyue Guo , Jan Obloj

An efficient $hp$-multigrid scheme is presented for local discontinuous Galerkin (LDG) discretizations of elliptic problems, formulated around the idea of separately coarsening the underlying discrete gradient and divergence operators. We…

Numerical Analysis · Mathematics 2019-03-14 Daniel Fortunato , Chris H. Rycroft , Robert Saye

We propose a generalized Eulerian-Lagrangian (GEL) discontinuous Galerkin (DG) method. The method is a generalization of the Eulerian-Lagrangian (EL) DG method for transport problems proposed in [arXiv preprint arXiv: 2002.02930 (2020)],…

Numerical Analysis · Mathematics 2022-06-08 Xue Hong , Jing-Mei Qiu

This work focuses on a class of elliptic boundary value problems with diffusive, advective and reactive terms, motivated by the study of three-dimensional heterogeneous physical systems composed of two or more media separated by a selective…

Numerical Analysis · Mathematics 2018-04-20 Riccardo Sacco , Aurelio Giancarlo Mauri , Giovanna Guidoboni

First, let $u_{g}$ be the unique solution of an elliptic variational inequality with source term $g$. We establish, in the general case, the error estimate between $u_{3}(\mu)=\mu u_{g_{1}}+ (1-\mu)u_{g_{2}}$ %(the convex combination of two…

Analysis of PDEs · Mathematics 2013-09-20 Mahdi Boukrouche , Domingo A. Tarzia

Several important problems in partial differential equations can be formulated as integral equations. Often the integral operator defines the solution of an elliptic problem with specified jump conditions at an interface. In principle the…

Numerical Analysis · Mathematics 2020-02-10 J. Thomas Beale , Wenjun Ying

The study of optimal control problems under uncertainty plays an important role in scientific numerical simulations. This class of optimization problems is strongly utilized in engineering, biology and finance. In this paper, a stochastic…

Optimization and Control · Mathematics 2023-04-06 Caroline Geiersbach , Teresa Scarinci

As an alternative to PINNs, a Deep Ritz framework is proposed to solve fully nonlinear PDEs. A least-squares algorithm is advocated to decouple the nonlinearities from the variational features of several fully nonlinear PDEs. A splitting…

Numerical Analysis · Mathematics 2026-05-01 Alexandre Caboussat , Martin T. Leclercq , Anna Peruso

Method-of-lines discretizations are demanding test problems for stiff integration methods. However, for PDE problems with known analytic solution the presence of space discretization errors or the need to use codes to compute reference…

Numerical Analysis · Mathematics 2023-05-24 Jens Lang , Bernhard A. Schmitt

A spacetime discontinuous Petrov-Galerkin (DPG) method for the linear wave equation is presented. This method is based on a weak formulation that uses a broken graph space. The wellposedness of this formulation is established using a…

Numerical Analysis · Mathematics 2018-10-09 Jay Gopalakrishnan , Paulina Sepulveda

Many inverse problems have to deal with complex, evolving and often not exactly known geometries, e.g. as domains of forward problems modeled by partial differential equations. This makes it desirable to use methods which are robust with…

Numerical Analysis · Mathematics 2015-07-13 Martin Burger , Ole Loseth Elvetun , Matthias Schlottbom

We develop, analyze, and experimentally explore residual-based loss functions for machine learning of parameter-to-solution maps in the context of parameter-dependent families of partial differential equations (PDEs). Our primary concern is…

Numerical Analysis · Mathematics 2025-06-24 Pablo Cortés Castillo , Wolfgang Dahmen , Jay Gopalakrishnan