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In this paper, we present a meshless hybrid method combining the Generalized Finite Difference (GFD) and Finite Difference based Radial Basis Function (RBF-FD) approaches to solve non-homogeneous partial differential equations (PDEs)…

Numerical Analysis · Mathematics 2025-05-02 Priyal Garg , T. V. S. Sekhar

We develop efficient and high-order accurate finite difference methods for elliptic partial differential equations in complex geometry in the Difference Potentials framework. The main novelty of the developed schemes is the use of local…

Numerical Analysis · Mathematics 2023-06-28 Qing Xia

Much effort has been put into developing samplers with specific properties, such as producing blue noise, low-discrepancy, lattice or Poisson disk samples. These samplers can be slow if they rely on optimization processes, may rely on a…

Diffusion models have shown remarkable empirical success in sampling from rich multi-modal distributions. Their inference relies on numerically solving a certain differential equation. This differential equation cannot be solved in closed…

Machine Learning · Computer Science 2026-01-16 Khashayar Gatmiry , Sitan Chen , Adil Salim

In this present paper we consider a full divergence-free of high order virtual finite element algorithm to approximate the stationary inductionless magnetohydrodynamic model on polygonal meshes. More precisely, we choice appropriate virtual…

Analysis of PDEs · Mathematics 2023-10-19 Xianghai Zhou , Haiyan Su

We construct incompressible velocity fields that exhibit faster than exponential dissipation for particular solutions to the advection-diffusion equation on $\mathbb{T}^d$. In 2D, we construct a velocity field in $L^\infty_{t,x}$ and…

Analysis of PDEs · Mathematics 2025-09-03 Keefer Rowan

Quantum mechanical methods based on the density functional theory (DFT) offer a realistic possibility of first-principles design of organic donor-acceptor systems and engineered band-gap materials. This promise is contingent upon the…

Chemical Physics · Physics 2013-12-03 Marcin Modrzejewski , Grzegorz Chałasiński , Małgorzata M. Szczęśniak

We study conformal field theory in $d=1$ space-time dimensions. We derive a dispersion relation for the 4-point correlation function of identical bosons and fermions, in terms of the double discontinuity. This extends the conformal…

High Energy Physics - Theory · Physics 2025-01-10 Dean Carmi , Sudip Ghosh , Trakshu Sharma

We consider the initial/boundary value problem for a diffusion equation involving multiple time-fractional derivatives on a bounded convex polyhedral domain. We analyze a space semidiscrete scheme based on the standard Galerkin finite…

Numerical Analysis · Mathematics 2015-06-18 Bangti Jin , Raytcho Lazarov , Yikan Liu , Zhi Zhou

Highly concentrated functions play an important role in many research fields including control system analysis and physics, and they turned out to be the key idea behind inverse Laplace transform methods as well. This paper uses the…

Performance · Computer Science 2019-01-28 Gabor Horvath , Illes Horvath , Miklos Telek

The purpose of this research is to describe an efficient iterative method suitable for obtaining high accuracy solutions to high frequency time-harmonic scattering problems. The method allows for both refinement of local polynomial degree…

Computational Physics · Physics 2018-12-26 Ryan Galagusz , Steve McFee

In this work, we explore a time-fractional diffusion equation of order $\alpha \in (0,1)$ with a stochastic diffusivity parameter. We focus on efficient estimation of the expected values (considered as an infinite dimensional integral on…

Numerical Analysis · Mathematics 2024-09-04 Josef Dick , Hecong Gao , William McLean , Kassem Mustapha

Diffusion models are state-of-the-art generative models, yet their samples often fail to satisfy application objectives such as safety constraints or domain-specific validity. Existing techniques for alignment require gradients, internal…

Diffusion models have emerged as powerful generative tools with applications in computer vision and scientific machine learning (SciML), where they have been used to solve large-scale probabilistic inverse problems. Traditionally, these…

We construct finite-dimensional approximations of solution spaces of divergence form operators with $L^\infty$-coefficients. Our method does not rely on concepts of ergodicity or scale-separation, but on the property that the solution space…

Numerical Analysis · Mathematics 2011-08-05 Houman Owhadi , Lei Zhang

Generative models for 3D molecular conformations must respect Euclidean symmetries and concentrate probability mass on thermodynamically favorable, mechanically stable structures. However, E(3)-equivariant diffusion models often reproduce…

Machine Learning · Computer Science 2026-01-30 Yunyang Li , Lin Huang , Luojia Xia , Wenhe Zhang , Mark Gerstein

This work is on a fast and accurate reduced basis method for solving discretized fractional elliptic partial differential equations (PDEs) of the form $\mathcal{A}^su=f$ by rational approximation. A direct computation of the action of such…

Numerical Analysis · Mathematics 2026-02-24 Yuwen Li , Ludmil T. Zikatanov , Cheng Zuo

Recent literature has effectively leveraged diffusion models trained on continuous variables as priors for solving inverse problems. Notably, discrete diffusion models with discrete latent codes have shown strong performance, particularly…

Computer Vision and Pattern Recognition · Computer Science 2025-09-22 Naoki Murata , Chieh-Hsin Lai , Yuhta Takida , Toshimitsu Uesaka , Bac Nguyen , Stefano Ermon , Yuki Mitsufuji

The hp-version of the finite element method is applied to singularly perturbed reaction-diffusion type equations on polygonal domains. The solution exhibits boundary layers as well as corner layers. On a class of meshes that are suitable…

Numerical Analysis · Mathematics 2018-03-07 Jens Markus Melenk , Markus Faustmann

The problem of eliminating fast-relaxing variables to obtain an effective drift-diffusion process in position is solved in a uniform and straightforward way for models with velocity a function jointly of position and fast variables. A more…

Statistical Mechanics · Physics 2019-11-13 Paul E. Lammert