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We provide a preliminary comparison of the dispersion properties, specifically the time-amplification factor, the scaled group velocity and the error in the phase speed of four spatiotemporal discretization schemes utilized for solving the…

Numerical Analysis · Mathematics 2019-12-23 S. Singh , S. Sircar

We present a finite element implementation for the steady-state nonlocal Dirichlet problem with homogeneous volume constraints. Here, the nonlocal diffusion operator is defined as integral operator characterized by a certain kernel…

Analysis of PDEs · Mathematics 2019-09-20 Christian Vollmann , Volker Schulz

We propose a novel supervised learning method to optimize the kernel in the maximum mean discrepancy generative adversarial networks (MMD GANs), and the kernel support vector machines (SVMs). Specifically, we characterize a distributionally…

Machine Learning · Computer Science 2020-02-25 Masoud Badiei Khuzani , Liyue Shen , Shahin Shahrampour , Lei Xing

A kernel based method is proposed for the construction of signature (defining) functions of subsets of $\mathbb{R}^d$. The subsets can range from full dimensional manifolds (open subsets) to point clouds (a finite number of points) and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Patrick Guidotti

In this paper we develop a class of efficient Galerkin boundary element methods for the solution of two-dimensional exterior single-scattering problems. Our approach is based upon construction of Galerkin approximation spaces confined to…

Numerical Analysis · Mathematics 2018-01-16 Fatih Ecevit , Hasan Hüseyin Eruslu

Most models of generative AI for images assume that images are inherently low-dimensional objects embedded within a high-dimensional space. Additionally, it is often implicitly assumed that thematic image datasets form smooth or piecewise…

Computer Vision and Pattern Recognition · Computer Science 2026-01-16 Leah Bar , Liron Mor Yosef , Shai Zucker , Neta Shoham , Inbar Seroussi , Nir Sochen

In this paper, we propose a mesh-free numerical method for solving elliptic PDEs on unknown manifolds, identified with randomly sampled point cloud data. The PDE solver is formulated as a spectral method where the test function space is the…

Numerical Analysis · Mathematics 2023-05-03 Qile Yan , Shixiao Jiang , John Harlim

This article investigates the non-stationary reaction-diffusion-advection equation, emphasizing solutions with internal layers and the associated inverse problems. We examine a nonlinear singularly perturbed partial differential equation…

Numerical Analysis · Mathematics 2025-02-06 Dmitrii Chaikovskii , Ye Zhang , Aleksei Liubavin

We present a quasi-conforming embedded reproducing kernel particle method (QCE-RKPM) for modeling heterogeneous materials that makes use of techniques not available to mesh-based methods such as the finite element method (FEM) and avoids…

Computational Engineering, Finance, and Science · Computer Science 2023-04-14 Ryan T. Schlinkman , Jonghyuk Baek , Frank N. Beckwith , Stacy M. Nelson , J. S. Chen

An adpative integration technique for time advancement of particle motion in the context of coupled computational fluid dynamics (CFD) - discrete element method (DEM) simulations is presented in this work. CFD-DEM models provide an accurate…

Computational Physics · Physics 2018-02-28 Hariswaran Sitaraman , Ray Grout

Non-linear convection-reaction-diffusion (CRD) partial differential equations (PDEs) are crucial for modeling complex phenomena in fields such as biology, ecology, population dynamics, physics, and engineering. Numerical approximation of…

Computational Physics · Physics 2025-05-06 Fardous Hasan , Hazrat Ali , Hasan Asyari Arief

Diffusion Probabilistic Models (DPMs) have emerged as a powerful class of deep generative models, achieving remarkable performance in image synthesis tasks. However, these models face challenges in terms of widespread adoption due to their…

Computer Vision and Pattern Recognition · Computer Science 2024-06-03 Kidist Amde Mekonnen , Nicola Dall'Asen , Paolo Rota

We present our deep learning framework to solve and accelerate the Time-Dependent partial differential equation's solution of one and two spatial dimensions. We demonstrate DiffusionNet solver by solving the 2D transient heat conduction…

Machine Learning · Computer Science 2020-11-20 Mahmoud Asem

In this paper we develop a numerical scheme based on quadratures to approximate solutions of integro-differential equations involving convolution kernels, $\nu$, of diffusive type. In particular, we assume $\nu$ is symmetric and…

Numerical Analysis · Mathematics 2020-11-03 Loic Cappanera , Gabriela Jaramillo , Cory Ward

High-dimensional data are often assumed to lie on lower-dimensional manifolds. We study how to construct diffusion processes on this data manifold using only point cloud samples and without access to charts, projections, or other geometric…

Machine Learning · Computer Science 2026-05-21 Victor Kawasaki-Borruat , Clara Grotehans , Pierre Vandergheynst , Adam Gosztolai

Algebraic topology methods have recently played an important role for statistical analysis with complicated geometric structured data such as shapes, linked twist maps, and material data. Among them, \textit{persistent homology} is a…

Machine Learning · Statistics 2018-10-30 Tam Le , Makoto Yamada

Numerical solution of nonlocal constrained value problems with integrable kernels are considered. These nonlocal problems arise in nonlocal mechanics and nonlocal diffusion. The structure of the true solution to the problem is analyzed…

Numerical Analysis · Mathematics 2019-02-26 Qiang Du , Xiaobo Yin

In this work, we investigate the $hp$-discontinuous Galerkin (DG) time-stepping method for the generalized Burgers-Huxley equation with memory, a non-linear advection-diffusion-reaction problem featuring weakly singular kernels. We derive a…

Numerical Analysis · Mathematics 2024-09-04 Sumit Mahajan , Arbaz Khan

We present a high-order radial basis function finite difference (RBF-FD) framework for the solution of advection-diffusion equations on time-varying domains. Our framework is based on a generalization of the recently developed Overlapped…

Numerical Analysis · Mathematics 2021-09-15 Varun Shankar , Grady B. Wright , Aaron L. Fogelson

The article discusses the gradient discretisation method (GDM) for distributed optimal control problems governed by diffusion equation with pure Neumann boundary condition. Using the GDM framework enables to develop an analysis that…

Numerical Analysis · Mathematics 2018-10-09 Jerome Droniou , Neela Nataraj , Devika Shylaja