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This research explores neural network-based numerical approximation of two-dimensional convection-dominated singularly perturbed problems on square, circular, and elliptic domains. Singularly perturbed boundary value problems pose…

Numerical Analysis · Mathematics 2024-07-11 Gung-Min Gie , Youngjoon Hong , Chang-Yeol Jung , Dongseok Lee

The possibility of treating boundary conditions in terms of a bilocal dynamical field is formalized in terms of a boundary action. This allows for a simple path-integral perturbation theory approach to physical effects such as radiation…

High Energy Physics - Theory · Physics 2015-12-09 Dimitra Karabali , V. P. Nair

Monte Carlo PDE solvers have become increasingly popular for solving heat-related partial differential equations in geometry processing and computer graphics due to their robustness in handling complex geometries. While existing methods can…

Graphics · Computer Science 2026-04-24 Anchang Bao , Enya Shen , Jianmin Wang

This paper proposes a novel Machine Learning-based approach to solve a Poisson problem with mixed boundary conditions. Leveraging Graph Neural Networks, we develop a model able to process unstructured grids with the advantage of enforcing…

This paper proposes a collocation boundary element method based on the Burton--Miller method for solving transmission problems, which is rapidly convergent within the Krylov subspace solver framework. Our study enhances Burton--Miller-type…

Numerical Analysis · Mathematics 2025-01-17 Yasuhiro Matsumoto , Akihiro Yoshiki , Hiroshi Isakari

Conditional kernel mean embeddings are nonparametric models that encode conditional expectations in a reproducing kernel Hilbert space. While they provide a flexible and powerful framework for probabilistic inference, their performance is…

Machine Learning · Statistics 2018-11-09 Kelvin Hsu , Richard Nock , Fabio Ramos

We present an approach to handle Dirichlet type nonlocal boundary conditions for nonlocal diffusion models with a finite range of nonlocal interactions. Our approach utilizes a linear extrapolation of prescribed boundary data. A novelty is,…

Analysis of PDEs · Mathematics 2021-08-27 Hwi Lee , Qiang Du

Convolution is an important tool in the construction of positive definite kernels on a manifold. This contribution provides conditions on an $L^2$-positive definite and zonal kernel on the unit sphere of $\mathbb{C}^q$ in order that the…

Classical Analysis and ODEs · Mathematics 2015-02-16 Victor S. Barbosa , Valdir A. Menegatto

Quadrature formulas for spheres, the rotation group, and other compact, homogeneous manifolds are important in a number of applications and have been the subject of recent research. The main purpose of this paper is to study coordinate…

Numerical Analysis · Mathematics 2012-11-26 E. Fuselier , T. Hangelbroek , F. J. Narcowich , J. D. Ward , G. B. Wright

We prove that the spatial coagulation equation with bounded coagulation rate is well-posed for all times in a given class of kernels if the convection term of the underlying particle dynamics has divergence bounded below by a positive…

Functional Analysis · Mathematics 2011-02-21 Ismael Bailleul

Special case calculations are presented, which can be used to put restrictions on the general form of heat kernel coefficients for transmittal boundary conditions and for generalized bag boundary conditions.

High Energy Physics - Theory · Physics 2009-11-07 Klaus Kirsten

There is a need for covariant solutions of bound state equations in order to construct realistic QCD based models of mesons and baryons. Furthermore, we ideally need to know the structure of these bound states in all kinematical regimes,…

High Energy Physics - Phenomenology · Physics 2007-05-23 A. G. Williams , K. Kusaka , K. M. Simpson

In this paper, we propose a numerical method to approximate the solution of partial differential equations in irregular domains with no-flux boundary conditions by means of spectral methods. The main features of this method are its…

Numerical Analysis · Mathematics 2007-05-23 Alfonso Bueno-Orovio , Victor M. Perez-Garcia , Flavio H. Fenton

The search for the optimal shape parameter for Radial Basis Function (RBF) kernel approximation has been an outstanding research problem for decades. In this work, we establish a theoretical framework for this problem by leveraging a…

Numerical Analysis · Mathematics 2026-01-21 Tizian Wenzel , Gabriele Santin

This paper proposed a novel radial basis function neural network (RBFNN) to solve various partial differential equations (PDEs). In the proposed RBF neural networks, the physics-informed kernel functions (PIKFs), which are derived according…

Numerical Analysis · Mathematics 2023-06-08 Zhuojia Fu , Wenzhi Xu , Shuainan Liu

Physics-Informed Neural Networks with hard constraints (HC-PINNs) are increasingly favored for their ability to strictly enforce boundary conditions via a trial function ansatz $\tilde{u} = A + B \cdot N$, yet the theoretical mechanisms…

Machine Learning · Computer Science 2025-12-30 Yuchen Xie , Honghang Chi , Haopeng Quan , Yahui Wang , Wei Wang , Yu Ma

In particle-based stochastic reaction-diffusion models, reaction rate and placement kernels are used to decide the probability per time a reaction can occur between reactant particles, and to decide where product particles should be placed.…

Quantitative Methods · Quantitative Biology 2022-06-08 Ying Zhang , Samuel A. Isaacson

Learning models of dynamical systems characterized by specific stability properties is of crucial importance in applications. Existing results mainly focus on linear systems or some limited classes of nonlinear systems and stability…

Systems and Control · Electrical Eng. & Systems 2025-03-18 Matteo Scandella , Michelangelo Bin , Thomas Parisini

We study the well-posedness for initial boundary value problems associated with time fractional diffusion equations with non-homogenous boundary and initial values. We consider both weak and strong solutions for the problems. For weak…

Analysis of PDEs · Mathematics 2020-04-30 Yavar Kian , Masahiro Yamamoto

For a class of one-dimensional determinantal point processes including those induced by orthogonal projections with integrable kernels satisfying a growth condition, it is proved that their conditional measures, with respect to the…

Probability · Mathematics 2016-05-05 Alexander I. Bufetov