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We numerically validate the Virtual Element Method of order k for general second order elliptic problems with variable coefficients in three dimensions. Moreover, we investigate numerically also the Serendipity version of the VEM (in three…

Numerical Analysis · Mathematics 2017-10-10 Lourenco Beirao da Veiga , Franco Brezzi , Franco Dassi , Luisa Donatella Marini , Alessandro Russo

We introduce variational spectral learning (VSL), a machine learning framework for solving partial differential equations (PDEs) that operates directly in the coefficient space of spectral expansions. VSL offers a principled bridge between…

Numerical Analysis · Mathematics 2026-01-07 M. M. Hammad

In this paper, we examine a finite element approximation of the steady $p(\cdot)$-Navier-Stokes equations ($p(\cdot)$ is variable dependent) and prove orders of convergence by assuming natural fractional regularity assumptions on the…

Numerical Analysis · Mathematics 2024-11-15 Luigi C. Berselli , Alex Kaltenbach

Score-based methods are powerful across machine learning, but they face a paradox: theoretically path-independent, yet practically path-dependent. We resolve this by proving that practical training objectives differ from the ideal,…

Machine Learning · Computer Science 2026-05-12 Wei Chen , Jiacheng Li , Shigui Li , Zhiqi Lin , Junmei Yang , John Paisley , Delu Zeng

Green's functions characterize the fundamental solutions of partial differential equations; they are essential for tasks ranging from shape analysis to physical simulation, yet they remain computationally prohibitive to evaluate on…

Graphics · Computer Science 2026-02-16 Joao Teixeira , Eitan Grinspun , Otman Benchekroun

When a sequence of numbers is slowly converging, it can be transformed into a new sequence which, under some assumptions, could converge faster to the same limit. One of the most well--known sequence transformation is Shanks transformation…

Numerical Analysis · Mathematics 2014-02-13 Claude Brezinski , Michela Redivo-Zaglia

Approximate necessary optimality conditions in terms of Fr\'echet subgradients and normals for a rather general optimization problem with a potentially non-Lipschitzian objective function are established with the aid of Ekeland's…

Optimization and Control · Mathematics 2021-10-15 Alexander Y. Kruger , Patrick Mehlitz

Recently, Stochastic Variational Inference (SVI) has been increasingly attractive thanks to its ability to find good posterior approximations of probabilistic models. It optimizes the variational objective with stochastic optimization,…

Machine Learning · Computer Science 2022-03-16 Minta Liu , Suliang Bu

A variational method is discussed, extending the Gaussian effective potential to higher orders. The single variational parameter is replaced by trial unknown two-point functions, with infinite variational parameters to be optimized by the…

High Energy Physics - Phenomenology · Physics 2013-09-30 Fabio Siringo

In this work, we develop variational formulations of Petrov-Galerkin type for one-dimensional fractional boundary value problems involving either a Riemann-Liouville or Caputo derivative of order $\alpha\in(3/2, 2)$ in the leading term and…

Numerical Analysis · Mathematics 2015-12-18 Bangti Jin , Raytcho Lazarov , Zhi Zhou

We prove H\"ormander's type hypoellipticity theorem for stochastic partial differential equations when the coefficients are only measurable with respect to the time variable. The need for such kind of results comes from filtering theory of…

Probability · Mathematics 2014-03-12 N. V. Krylov

A partial order on the set of metric measure spaces is defined; it generalizes the Lipschitz order of Gromov. We show that our partial order is closed when metric measure spaces are equipped with the Gromov-weak topology and give a new…

Probability · Mathematics 2016-05-31 Max Grieshammer , Thomas Rippl

The solution of pseudo initial value differential equations, either ordinary or partial (including those of fractional nature), requires the development of adequate analytical methods, complementing those well established in the ordinary…

Mathematical Physics · Physics 2019-02-05 Nicolas Behr , Giuseppe Dattoli , Ambra Lattanzi

The Energy-Dissipation Principle provides a variational tool for the analysis of parabolic evolution problems: solutions are characterized as so-called null-minimizers of a global functional on entire trajectories. This variational…

Analysis of PDEs · Mathematics 2021-09-14 Luca Scarpa , Ulisse Stefanelli

This work is devoted to averaging principle of a two-time-scale stochastic partial differential equation on a bounded interval $[0, l]$, where both the fast and slow components are directly perturbed by additive noises. Under some regular…

Probability · Mathematics 2018-02-06 Hongbo Fu , Li Wan , Jicheng Liu , Xianming Liu

We introduce a new numerical method, based on Bernoulli polynomials, for solving multiterm variable-order fractional differential equations. The variable-order fractional derivative was considered in the Caputo sense, while the…

Numerical Analysis · Mathematics 2021-11-18 Somayeh Nemati , Pedro M. Lima , Delfim F. M. Torres

This paper is devoted to find the numerical solutions of one dimensional general nonlinear system of third-order boundary value problems (BVPs) for the pair of functions using Galerkin weighted residual method. We derive mathematical…

Numerical Analysis · Mathematics 2024-04-24 Snigdha Dhar , Md. Shafiqul Islam

In this work we propose a novel approach to investigate boundary value problems (BVPs) for fully third order differential equations. It is based on the reduction of BVPs to operator equations for the nonlinear terms but not for the…

Numerical Analysis · Mathematics 2018-06-04 Dang Quang A , Dang Quang Long

We propose, as an alternative theory of quantum mechanics, a relativistically covariant variational principle (VP) capable of describing both wavefunction collapse and, as an appropriate limiting case, evolution of the wavefunction…

Quantum Physics · Physics 2012-04-19 Alan K. Harrison

We consider the problem of partial order production: arrange the elements of an unknown totally ordered set T into a target partially ordered set S, by comparing a minimum number of pairs in T. Special cases include sorting by comparisons,…

Data Structures and Algorithms · Computer Science 2010-05-06 Jean Cardinal , Samuel Fiorini , Gwenaël Joret , Raphaël M. Jungers , J. Ian Munro
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