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The discovery of Partial Differential Equations (PDEs) is an essential task for applied science and engineering. However, data-driven discovery of PDEs is generally challenging, primarily stemming from the sensitivity of the discovered…

Machine Learning · Statistics 2024-03-27 Aoxue Chen , Yifan Du , Liyao Mars Gao , Guang Lin

In this paper, we evaluate the effectiveness of deep operator networks (DeepONets) in solving both forward and inverse problems of partial differential equations (PDEs) on unknown manifolds. By unknown manifolds, we identify the manifold by…

Numerical Analysis · Mathematics 2024-07-09 Anran Jiao , Qile Yan , Jhn Harlim , Lu Lu

Interior point methods (IPMs) are a common approach for solving linear programs (LPs) with strong theoretical guarantees and solid empirical performance. The time complexity of these methods is dominated by the cost of solving a linear…

Optimization and Control · Mathematics 2022-02-04 Gregory Dexter , Agniva Chowdhury , Haim Avron , Petros Drineas

Identifying unknown differential equations from a given set of discrete time dependent data is a challenging problem. A small amount of noise can make the recovery unstable, and nonlinearity and differential equations with varying…

Numerical Analysis · Mathematics 2019-04-09 Sung Ha Kang , Wenjing Liao , Yingjie Liu

In this paper, we present a novel pseudospectral (PS) method for solving a new class of initial-value problems (IVPs) of time-dependent one-dimensional fractional partial differential equations (FPDEs) with variable coefficients and…

Numerical Analysis · Mathematics 2023-12-11 Kareem T. Elgindy

Inverse problems in partial differential equations (PDEs) involve estimating the physical parameters of a system from observed spatiotemporal solution fields. Neural networks are well-suited for PDE parameter estimation due to their…

Machine Learning · Computer Science 2026-05-27 Divyam Goel , Nithin Chalapathi , Sanjeev Raja , Aditi S. Krishnapriyan

We construct least squares formulations of PDEs with inhomogeneous essential boundary conditions, where boundary residuals are not measured in unpractical fractional Sobolev norms, but which formulations nevertheless are shown to yield a…

Numerical Analysis · Mathematics 2025-05-12 Harald Monsuur , Robin Smeets , Rob Stevenson

We discuss various compatibility criteria for overdetermined systems of PDEs generalizing the approach to formal integrability via brackets of differential operators. Then we give sufficient conditions that guarantee that a PDE possessing a…

Differential Geometry · Mathematics 2012-03-06 Boris Kruglikov

The optimization problems with simple bounds are an important class of problems. To facilitate the computation of such problems, an unconstrained-like dynamic method, motivated by the Lyapunov control principle, is proposed. This method…

Optimization and Control · Mathematics 2021-10-19 Sheng Zhang , Xin Du , Fang-Fang Hu , Jiang-Tao Huang

Finding sparse solutions of underdetermined systems of linear equations is a fundamental problem in signal processing and statistics which has become a subject of interest in recent years. In general, these systems have infinitely many…

Machine Learning · Statistics 2010-09-21 Arash Ali Amini , Massoud Babaie-Zadeh , Christian Jutten

This paper introduces a computationally efficient algorithm in system theory for solving inverse problems governed by linear partial differential equations (PDEs). We model solutions of linear PDEs using Gaussian processes with priors…

Machine Learning · Statistics 2025-06-16 Xin Li , Markus Lange-Hegermann , Bogdan Raiţă

This paper studies bulk-surface splitting methods of first order for (semi-linear) parabolic partial differential equations with dynamic boundary conditions. The proposed Lie splitting scheme is based on a reformulation of the problem as a…

Numerical Analysis · Mathematics 2021-08-19 Robert Altmann , Balázs Kovács , Christoph Zimmer

The traditional limitations of neural networks in reliably generalizing beyond the convex hulls of their training data present a significant problem for computational physics, in which one often wishes to solve PDEs in regimes far beyond…

Machine Learning · Computer Science 2026-02-17 Jonathan Gorard , Ammar Hakim , James Juno

Methods for solving scientific computing and inference problems, such as kernel- and neural network-based approaches for partial differential equations (PDEs), inverse problems, and supervised learning tasks, depend crucially on the choice…

Machine Learning · Statistics 2025-10-08 Nicholas H. Nelsen , Houman Owhadi , Andrew M. Stuart , Xianjin Yang , Zongren Zou

A new iterative technique is presented for solving of initial value problem for certain classes of multidimensional linear and nonlinear partial differential equations. Proposed iterative scheme does not require any discretization,…

Numerical Analysis · Mathematics 2016-02-23 Josef Rebenda , Zdeněk Šmarda

We consider compact finite-difference schemes of the 4th approximation order for an initial-boundary value problem (IBVP) for the $n$-dimensional non-homogeneous wave equation, $n\geq 1$. Their construction is accomplished by both the…

Numerical Analysis · Mathematics 2025-12-30 Alexander Zlotnik , Olga Kireeva

We apply the theory of Lie point symmetries for the study of a family of partial differential equations which are integrable by the hyperbolic reductions method and are reduced to members of the Painlev\'{e} transcendents. The main results…

Exactly Solvable and Integrable Systems · Physics 2022-08-08 Andronikos Paliathanasis

Parabolic partial differential equations (PDEs) appear in many disciplines to model the evolution of various mathematical objects, such as probability flows, value functions in control theory, and derivative prices in finance. It is often…

Machine Learning · Computer Science 2024-07-18 Xingzi Xu , Ali Hasan , Jie Ding , Vahid Tarokh

In this article, we consider linear hyperbolic Initial and Boundary Value Problems (IBVP) in a rectangle (or possibly curvilinear polygonal domains) in both the constant and variable coefficients cases. We use semigroup method instead of…

Analysis of PDEs · Mathematics 2013-10-23 Aimin Huang , Roger Temam

Simulations of physical phenomena are essential to the expedient design of precision components in aerospace and other high-tech industries. These phenomena are often described by mathematical models involving partial differential equations…

Computational Physics · Physics 2017-01-05 Daniel Magee , Kyle E Niemeyer