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We consider a class of linear differential operators acting on vector-valued function spaces with general coupled boundary conditions. Unlike in the more usual case of so-called quantum graphs, the boundary conditions can be nonlinear.…

Analysis of PDEs · Mathematics 2018-12-21 Delio Mugnolo , René Pröpper

Several algorithms in computer algebra involve the computation of a power series solution of a given ordinary differential equation. Over finite fields, the problem is often lifted in an approximate $p$-adic setting to be well-posed. This…

Symbolic Computation · Computer Science 2023-06-12 Pierre Lairez , Tristan Vaccon

Functional data describe a wide range of processes, such as growth curves and spectral absorption. In this study, we analyze air pollution data from the In-service Aircraft for a Global Observing System, focusing on the spatial interactions…

Methodology · Statistics 2024-11-14 Rita Fici , Gianluca Sottile , Luigi Augugliaro , Ernst-Jan Camiel Wit

For more than two centuries, solutions of differential equations have been obtained either analytically or numerically based on typically well-behaved forcing and boundary conditions for well-posed problems. We are changing this paradigm in…

Machine Learning · Computer Science 2017-03-08 Maziar Raissi , Paris Perdikaris , George Em. Karniadakis

We present a data-driven machine-learning approach for modeling space-time socioeconomic dynamics. Through coarse-graining fine-scale observations, our modeling framework simplifies these complex systems to a set of tractable mechanistic…

Machine Learning · Computer Science 2024-07-26 James Koch , Pranab Roy Chowdhury , Heng Wan , Parin Bhaduri , Jim Yoon , Vivek Srikrishnan , W. Brent Daniel

Instrumental variables have proven useful, in particular within the social sciences and economics, for making inference about the causal effect of a random variable, B, on another random variable, C, in the presence of unobserved…

Methodology · Statistics 2012-06-26 Roland R. Ramsahai

We develop a framework for Gaussian processes regression constrained by boundary value problems. The framework may be applied to infer the solution of a well-posed boundary value problem with a known second-order differential operator and…

Machine Learning · Computer Science 2020-12-23 Mamikon Gulian , Ari Frankel , Laura Swiler

This chapter of the forthcoming Handbook of Graphical Models contains an overview of basic theorems and techniques from algebraic geometry and how they can be applied to the study of conditional independence and graphical models. It also…

Statistics Theory · Mathematics 2017-05-23 Thomas Kahle , Johannes Rauh , Seth Sullivant

The question of boundary conditions in conformal field theories is discussed, in the light of recent progress. Two kinds of boundary conditions are examined, along open boundaries of the system, or along closed curves or ``seams''. Solving…

High Energy Physics - Theory · Physics 2017-08-23 V. B. Petkova , J. -B. Zuber

Border bases are a generalization of Gr\"obner bases for zero-dimensional ideals in polynomial rings. In this article, we introduce border bases for a non-commutative ring of linear differential operators, namely the rational Weyl algebra.…

Algebraic Geometry · Mathematics 2026-02-13 Carlos Rodriguez , Anna-Laura Sattelberger

In spatially extended systems, it is common to find latent variables that are hard, or even impossible, to measure with acceptable precision, but are crucially important for the proper description of the dynamics. This substantially…

Numerical Analysis · Computer Science 2019-08-28 Patrick A. K. Reinbold , Roman O. Grigoriev

We present an end-to-end framework to learn partial differential equations that brings together initial data production, selection of boundary conditions, and the use of physics-informed neural operators to solve partial differential…

Computational Physics · Physics 2023-08-21 Shawn G. Rosofsky , Hani Al Majed , E. A. Huerta

The peridynamic theory reformulates the equations of continuum mechanics in terms of integro-differential equations instead of partial differential equations. It is not trivial to directly apply naive approach in artificial boundary…

Computational Engineering, Finance, and Science · Computer Science 2021-07-07 Songsong Ji , Gang Pang , Jiwei Zhang , Yibo Yang , Paris Perdikaris

We present a form of algebraic reasoning for computational objects which are expressed as graphs. Edges describe the flow of data between primitive operations which are represented by vertices. These graphs have an interface made of…

Logic in Computer Science · Computer Science 2010-07-23 Lucas Dixon , Ross Duncan , Aleks Kissinger

We propose a method combining boundary integral equations and neural networks (BINet) to solve partial differential equations (PDEs) in both bounded and unbounded domains. Unlike existing solutions that directly operate over original PDEs,…

Numerical Analysis · Mathematics 2021-10-04 Guochang Lin , Pipi Hu , Fukai Chen , Xiang Chen , Junqing Chen , Jun Wang , Zuoqiang Shi

We present a method for rejecting competing models from noisy time-course data that does not rely on parameter inference. First we characterize ordinary differential equation models in only measurable variables using differential algebra…

Dynamical Systems · Mathematics 2016-04-04 Heather A. Harrington , Kenneth L. Ho , Nicolette Meshkat

We introduce priors and algorithms to perform Bayesian inference in Gaussian models defined by acyclic directed mixed graphs. Such a class of graphs, composed of directed and bi-directed edges, is a representation of conditional…

Methodology · Statistics 2012-07-02 Ricardo Silva , Zoubin Ghahramani

We characterize the behavior of the solutions of linear evolution partial differential equations on the half line in the presence of discontinuous initial conditions or discontinuous boundary conditions, as well as the behavior of the…

Analysis of PDEs · Mathematics 2017-07-26 Gino Biondini , Thomas Trogdon

Gaussian processes (GPs) provide a powerful framework for extrapolation, interpolation, and noise removal in regression and classification. This paper considers constraining GPs to arbitrarily-shaped domains with boundary conditions. We…

Machine Learning · Statistics 2019-04-11 Arno Solin , Manon Kok

We review our algebraic framework for linear boundary problems (concentrating on ordinary differential equations). Its starting point is an appropriate algebraization of the domain of functions, which we have named integro-differential…

Symbolic Computation · Computer Science 2012-10-11 Markus Rosenkranz , Georg Regensburger , Loredana Tec , Bruno Buchberger