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Suppose we are given a pair of points $s, t$ and a set $S$ of $n$ geometric objects in the plane, called obstacles. We show that in polynomial time one can construct an auxiliary (multi-)graph $G$ with vertex set $S$ and every edge labeled…

Computational Geometry · Computer Science 2022-03-17 Neeraj Kumar , Daniel Lokshtanov , Saket Saurabh , Subhash Suri , Jie Xue

In this article we introduce a Partial Differential Equation (PDE) for the rank one convex envelope. Rank one convex envelopes arise in non-convex vector valued variational problems \cite{BallElasticity, kohn1986optimal1, BallJames87,…

Analysis of PDEs · Mathematics 2017-03-08 Adam M. Oberman , Yuanlong Ruan

Modeling the traffic dynamics is essential for understanding and predicting the traffic spatiotemporal evolution. However, deriving the partial differential equation (PDE) models that capture these dynamics is challenging due to their…

Systems and Control · Electrical Eng. & Systems 2025-05-05 Zihang Wei , Yunlong Zhang , Chenxi Liu , Yang Zhou

The paper develops the method for construction of families of particular solutions to some classes of nonlinear Partial Differential Equations (PDE). Method is based on the specific link between algebraic matrix equations and PDE.…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 A. I. Zenchuk

We develop a framework for estimating unknown partial differential equations from noisy data, using a deep learning approach. Given noisy samples of a solution to an unknown PDE, our method interpolates the samples using a neural network,…

Machine Learning · Computer Science 2019-10-24 Ali Hasan , João M. Pereira , Robert Ravier , Sina Farsiu , Vahid Tarokh

A point visibility graph is a graph induced by a set of points in the plane, where every vertex corresponds to a point, and two vertices are adjacent whenever the two corresponding points are visible from each other, that is, the open…

Computational Geometry · Computer Science 2019-02-05 Jean Cardinal , Udo Hoffmann

We consider an obstacle problem for (possibly non-local) wave equations, and we prove existence of weak solutions through a convex minimization approach based on a time discrete approximation scheme. We provide the corresponding numerical…

Analysis of PDEs · Mathematics 2019-01-24 Mauro Bonafini , Matteo Novaga , Giandomenico Orlandi

We prove the existence and uniqueness of solution of the obstacle problem for quasilinear Stochastic PDEs with non-homogeneous second order operator. Our method is based on analytical technics coming from the parabolic potential theory. The…

Probability · Mathematics 2013-01-08 Denis Laurent , Matoussi Anis , Zhang Jing

Parabolic partial differential equations (PDEs) and backward stochastic differential equations (BSDEs) have a wide range of applications. In particular, high-dimensional PDEs with gradient-dependent nonlinearities appear often in the…

Numerical Analysis · Mathematics 2022-04-18 Martin Hutzenthaler , Thomas Kruse

In this paper, we study a certain class of nonlocal partial differential equations (PDEs). The equations arise from a key problem in network science, i.e., network generation from local interaction rules, which result in a change of the…

Dynamical Systems · Mathematics 2020-12-11 Tobias Böhle , Christian Kuehn

We introduce a Monte Carlo method for computing derivatives of the solution to a partial differential equation (PDE) with respect to problem parameters (such as domain geometry or boundary conditions). Derivatives can be evaluated at…

Graphics · Computer Science 2024-09-19 Bailey Miller , Rohan Sawhney , Keenan Crane , Ioannis Gkioulekas

Surface partial differential equations arise in numerous scientific and engineering applications. Their numerical solution on static and evolving surfaces remains challenging due to geometric complexity and, for evolving geometries, the…

Numerical Analysis · Mathematics 2026-03-03 Jingbo Sun , Fei Wang

An automated framework is presented for the numerical solution of optimal control problems with PDEs as constraints, in both the stationary and instationary settings. The associated code can solve both linear and non-linear problems, and…

Numerical Analysis · Mathematics 2024-09-02 Santolo Leveque , James R. Maddison , John W. Pearson

The interpretation of numerical methods, such as finite difference methods for differential equations, as point estimators suggests that formal uncertainty quantification can also be performed in this context. Competing statistical…

Other Statistics · Statistics 2019-09-24 Junyang Wang , Jon Cockayne , Chris J. Oates

The study of symmetries of partial differential equations (PDEs) has been traditionally treated as a geometrical problem. Although geometrical methods have been proven effective with regard to finding infinitesimal symmetry transformations,…

Analysis of PDEs · Mathematics 2025-11-03 C. J. Papachristou

We prove the well-posedness results, i.e. existence, uniqueness, and stability, of the solutions to a class of nonlocal fully nonlinear parabolic partial differential equations (PDEs), where there is an external time parameter $t$ on top of…

Analysis of PDEs · Mathematics 2021-10-11 Qian Lei , Chi Seng Pun

In this paper we consider multi-dimensional partial differential equations of parabolic type involving divergence form operators that possess a discontinuous coefficient matrix along some smooth interface. The solution of the equation is…

Probability · Mathematics 2020-03-27 Pierre Etore , Miguel Martinez

We prove an existence and uniqueness result for Neumann boundary problem of a parabolic partial differential equation (PDE for short) with a singular nonlinear divergence term which can only be understood in a weak sense. A probabilistic…

Probability · Mathematics 2018-02-22 Xue Yang , Jing Zhang

Scientific machine learning has been successfully applied to inverse problems and PDE discovery in computational physics. One caveat concerning current methods is the need for large amounts of ("clean") data, in order to characterize the…

Numerical Analysis · Mathematics 2021-11-30 Christophe Bonneville , Christopher J. Earls

Identifying dynamical systems from experimental data is a notably difficult task. Prior knowledge generally helps, but the extent of this knowledge varies with the application, and customized models are often needed. Neural ordinary…

Systems and Control · Electrical Eng. & Systems 2023-01-13 Mona Buisson-Fenet , Valery Morgenthaler , Sebastian Trimpe , Florent Di Meglio