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In a series of papers Barron, Goebel, and Jensen studied Partial Differential Equations (PDE)s for quasiconvex (QC) functions \cite{barron2012functions, barron2012quasiconvex,barron2013quasiconvex,barron2013uniqueness}. To overcome the lack…

Analysis of PDEs · Mathematics 2019-02-08 Bilal Abbasi , Adam M. Oberman

The Convex Envelope of a given function was recently characterized as the solution of a fully nonlinear Partial Differential Equation (PDE). In this article we study a modified problem: the Dirichlet problem for the underlying PDE. The main…

Analysis of PDEs · Mathematics 2010-07-07 Luis Silvestre , Adam M. Oberman

A convex envelope for the problem of finding the best approximation to a given matrix with a prescribed rank is constructed. This convex envelope allows the usage of traditional optimization techniques when additional constraints are added…

Functional Analysis · Mathematics 2016-08-30 Fredrik Andersson , Marcus Carlsson , Carl Olsson

This paper presents a finite-dimensional approximation for a class of partial differential equations on the space of probability measures. These equations are satisfied in the sense of viscosity solutions. The main result states the…

Probability · Mathematics 2024-07-24 Mehdi Talbi

This paper presents an efficient algorithm for the approximation of the rank-one convex hull in the context of nonlinear solid mechanics. It is based on hierarchical rank-one sequences and simultaneously provides first and second derivative…

Computational Engineering, Finance, and Science · Computer Science 2024-05-28 Maximilian Köhler , Timo Neumeier , Malte. A. Peter , Daniel Peterseim , Daniel Balzani

This paper presents a mathematical analysis of an elliptic partial differential equation (PDE) designed to compute the geometric thickness of a given shape. The PDE-based formulation provides a direct and systematic approach to evaluate…

Analysis of PDEs · Mathematics 2025-11-18 Atsushi Nakayasu , Takayuki Yamada

The elliptic 2-Hessian equation is a fully nonlinear partial differential equation (PDE) that is related to intrinsic curvature for three dimensional manifolds. We introduce two numerical methods for this PDE: the first is provably…

Numerical Analysis · Mathematics 2016-02-11 Brittany D. Froese , Adam M. Oberman , Tiago Salvador

We introduce suitable coordinate systems for pipes and their variants that allow us to transform partial differential equations (PDEs) on the pipe surfaces or in the solid pipes into computational domains with fixed limits/ranges. Such a…

Numerical Analysis · Mathematics 2025-09-09 Shuaifei Hu , Yujian Jiao , Desong Kong , Li-Lian Wang

We develop two-scale methods for computing the convex envelope of a continuous function over a convex domain in any dimension.This hinges on a fully nonlinear obstacle formulation [A. M. Oberman, "The convex envelope is the solution of a…

Numerical Analysis · Mathematics 2019-01-01 Wenbo Li , Ricardo H. Nochetto

This paper presents computationally feasible rank-one relaxation algorithms for the efficient simulation of a time-incremental damage model with nonconvex incremental stress potentials in multiple spatial dimensions. While the standard…

Computational Engineering, Finance, and Science · Computer Science 2023-02-10 Daniel Balzani , Maximilian Köhler , Timo Neumeier , Malte A. Peter , Daniel Peterseim

We show that positively $1$--homogeneous rank one convex functions are convex at $0$ and at matrices of rank one. The result is a special case of an abstract convexity result that we establish for positively $1$--homogeneous directionally…

Analysis of PDEs · Mathematics 2016-03-23 Bernd Kirchheim , Jan Kristensen

The numerical solution methods for partial differential equation (PDE) solution allow obtaining a discrete field that converges towards the solution if the method is applied to the correct problem. Nevertheless, the numerical methods…

Numerical Analysis · Mathematics 2021-03-04 Alexander Hvatov

In this paper we establish a connection between non-convex optimization methods for training deep neural networks and nonlinear partial differential equations (PDEs). Relaxation techniques arising in statistical physics which have already…

Machine Learning · Computer Science 2017-06-05 Pratik Chaudhari , Adam Oberman , Stanley Osher , Stefano Soatto , Guillaume Carlier

We consider partial differential equations (PDEs) characterized by an upper barrier that depends on the solution itself and a fixed lower barrier, while accommodating a non-local driver. First, we show a Feynman-Kac representation for the…

Probability · Mathematics 2024-09-04 Magnus Perninge

This work proposes a systematic model reduction approach based on rank adaptive tensor recovery for partial differential equation (PDE) models with high-dimensional random parameters. Since the standard outputs of interest of these models…

Numerical Analysis · Mathematics 2019-02-15 Kejun Tang , Qifeng Liao

This article investigates the numerical approximation of shape optimization problems with PDE constraint on classes of convex domains. The convexity constraint provides a compactness property which implies well posedness of the problem.…

Optimization and Control · Mathematics 2018-10-26 Sören Bartels , Gerd Wachsmuth

For a class of partial differential algebraic equations (PDAEs) of quasi-linear type which include nonlinear terms of convection type a possibility to determine a time and spatial index is considered. As a typical example we investigate an…

Numerical Analysis · Mathematics 2013-03-19 Wenfried Lucht , Kristian Debrabant

We study fully nonlinear second-order (forward) stochastic partial differential equations (SPDEs). They can also be viewed as forward path-dependent PDEs (PPDEs) and will be treated as rough PDEs (RPDEs) under a unified framework. We…

Probability · Mathematics 2018-10-02 Rainer Buckdahn , Christian Keller , Jin Ma , Jianfeng Zhang

We introduce a framework for solving a class of parabolic partial differential equations on triangle mesh surfaces, including the Hamilton-Jacobi equation and the Fokker-Planck equation. PDE in this class often have nonlinear or stiff terms…

Numerical Analysis · Mathematics 2024-06-04 Leticia Mattos Da Silva , Oded Stein , Justin Solomon

This paper provides a rigorous convergence rate and complexity analysis for a recently introduced framework, called PDE acceleration, for solving problems in the calculus of variations, and explores applications to obstacle problems. PDE…

Numerical Analysis · Mathematics 2019-07-31 Jeff Calder , Anthony Yezzi
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