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We propose an efficient numerical strategy for simulating fluid flow through porous media with highly oscillatory characteristics. Specifically, we consider non-linear diffusion models. This scheme is based on the classical homogenization…

Numerical Analysis · Mathematics 2020-02-04 Manuela Bastidas , Carina Bringedal , Sorin Pop , Florin Radu

Statistical depth, which measures the center-outward rank of a given sample with respect to its underlying distribution, has become a popular and powerful tool in nonparametric inference. In this paper, we investigate the use of statistical…

Methodology · Statistics 2025-11-25 Chifeng Shen , Yuejiao Fu , Michael Chen , Xiaoping Shi

We propose an abstract framework for the homogenization of random functionals which may contain non-convex terms, based on a two-scale $\Gamma$-convergence approach and a definition of Young measures on micropatterns which encodes the…

Analysis of PDEs · Mathematics 2017-08-07 Leonid Berlyand , Etienne Sandier , Sylvia Serfaty

Numerical homogenization tries to approximate the solutions of elliptic partial differential equations with strongly oscillating coefficients by functions from modified finite element spaces. We present in this paper a class of such methods…

Numerical Analysis · Mathematics 2018-01-23 Ralf Kornhuber , Daniel Peterseim , Harry Yserentant

In this paper, an analytic approximation method for highly nonlinear equations, namely the homotopy analysis method (HAM), is employed to solve some backward stochastic differential equations (BSDEs) and forward-backward stochastic…

Numerical Analysis · Mathematics 2018-01-25 Xiaoxu Zhong , Shijun Liao

In this work we introduce and analyze a new multiscale method for strongly nonlinear monotone equations in the spirit of the Localized Orthogonal Decomposition. A problem-adapted multiscale space is constructed by solving linear local…

Numerical Analysis · Mathematics 2020-12-16 Barbara Verfürth

Asymptotic methods for hypothesis testing in high-dimensional data usually require the dimension of the observations to increase to infinity, often with an additional condition on its rate of increase compared to the sample size. On the…

Statistics Theory · Mathematics 2024-03-26 Joydeep Chowdhury , Subhajit Dutta , Marc G. Genton

Numerical Algebraic Geometry uses numerical data to describe algebraic varieties. It is based on the methods of numerical polynomial homotopy continuation, an alternative to the classical symbolic approaches of computational algebraic…

Algebraic Geometry · Mathematics 2011-11-23 Anton Leykin

There are three main types of numerical computations for the Bessel function of the second kind: series expansion, continued fraction, and asymptotic expansion. In addition, they are combined in the appropriate domain for each. However,…

Numerical Analysis · Mathematics 2021-09-09 Takashi Takekawa

We define graded Hopf algebras with bases labeled by various types of graphs and hypergraphs, provided with natural embeddings into an algebra of polynomials in infinitely many variables. These algebras are graded by the number of edges and…

Combinatorics · Mathematics 2008-12-19 Jean-Christophe Novelli , Jean-Yves Thibon , Nicolas M. Thiéry

The technique of periodic homogenization with two-scale convergence is applied to the analysis of a two-phase Stefan-type problem that arises in the study of a periodic array of melting ice bars. For this "reduced model" we prove results on…

Analysis of PDEs · Mathematics 2014-11-13 Isabell Graf , John M. Stockie

Asymptotic methods for hypothesis testing in high-dimensional data usually require the dimension of the observations to increase to infinity, often with an additional relationship between the dimension (say, $p$) and the sample size (say,…

Methodology · Statistics 2025-12-11 Ritabrata Karmakar , Joydeep Chowdhury , Subhajit Dutta , Marc G. Genton

We present an efficient method for the computation of homogenized coefficients of divergence-form operators with random coefficients. The approach is based on a multiscale representation of the homogenized coefficients. We then implement…

Numerical Analysis · Mathematics 2019-05-17 A. Hannukainen , J. -C. Mourrat , H. Stoppels

A central question in numerical homogenization of partial differential equations with multiscale coefficients is the accurate computation of effective quantities, such as the homogenized coefficients. Computing homogenized coefficients…

Numerical Analysis · Mathematics 2020-07-22 Assyr Abdulle , Doghonay Arjmand , Edoardo Paganoni

This paper explores Bayesian estimation for categorical data, focusing on simple yet effective models that provide a foundation for applying more advanced methods accurately and reliably in real-world applications. We begin by revisiting…

Methodology · Statistics 2025-09-03 Jan Kalina

We present monostatic sampling methods for limited-aperture scattering problems in two dimensions. The direct sampling method (DSM) is well known to provide a robust, stable, and fast numerical scheme for imaging inhomogeneities from…

Numerical Analysis · Mathematics 2022-04-14 Sangwoo Kang , Mikyoung Lim

We present numerical homotopy continuation algorithms for solving systems of equations on a variety in the presence of a finite Khovanskii basis. These take advantage of Anderson's flat degeneration to a toric variety. When Anderson's…

Algebraic Geometry · Mathematics 2020-09-01 Michael Burr , Frank Sottile , Elise Walker

Matrix congruence can be used to mimic linear maps between homogeneous quadratic polynomials in $n$ variables. We introduce a generalization, called standard-form congruence, which mimics affine maps between non-homogeneous quadratic…

Rings and Algebras · Mathematics 2018-09-19 Jason Gaddis

This paper discusses the theory and numerical method of two-scale analysis for the multiscale Landau-Lifshitz-Gilbert equation in composite ferromagnetic materials. The novelty of this work can be summarized in three aspects: Firstly, the…

Numerical Analysis · Mathematics 2024-03-25 Xiaofei Guan , Hang Qi , Zhiwei Sun

We consider the problem of symmetrising a neural network along a group homomorphism: given a homomorphism $\varphi : H \to G$, we would like a procedure that converts $H$-equivariant neural networks to $G$-equivariant ones. We formulate…

Machine Learning · Statistics 2025-01-10 Rob Cornish
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