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We study the problem of model aggregation within the Wasserstein space for probability measures on the real line. Given a fixed finite collection of candidate probability models, we consider the associated class of Wasserstein barycenters…

Based on the Multifractal Detrended Fluctuation Analysis (MFDFA) and on the Wavelet Transform Modulus Maxima (WTMM) methods we investigate the origin of multifractality in the time series. Series fluctuating according to a qGaussian…

Data Analysis, Statistics and Probability · Physics 2015-05-13 Stanislaw Drozdz , Jaroslaw Kwapien , Pawel Oswiecimka , Rafal Rak

This article performs a unified convergence analysis of a variety of numerical methods for a model of the miscible displacement of one incompressible fluid by another through a porous medium. The unified analysis is enabled through the…

Numerical Analysis · Mathematics 2018-03-07 Jérôme Droniou , Robert Eymard , Alain Prignet , Kyle S. Talbot

For an unknown continuous distribution on a real line, we consider the approximate estimation by the discretization. There are two methods for the discretization. First method is to divide the real line into several intervals before taking…

Statistics Theory · Mathematics 2017-10-12 Yo Sheena

Score-based methods have recently seen increasing popularity in modeling and generation. Methods have been constructed to perform hypothesis testing and change-point detection with score functions, but these methods are in general not as…

Machine Learning · Statistics 2025-06-23 Sean Moushegian , Taposh Banerjee , Vahid Tarokh

We develop a multipoint stress mixed finite element method for linear elasticity with weak stress symmetry on quadrilateral grids, which can be reduced to a symmetric and positive definite cell centered system. The method is developed on…

Numerical Analysis · Mathematics 2019-08-06 Ilona Ambartsumyan , Eldar Khattatov , Jan M. Nordbotten , Ivan Yotov

Sampling from unnormalized densities using diffusion models has emerged as a powerful paradigm. However, while recent approaches that use least-squares `matching' objectives have improved scalability, they often necessitate significant…

Machine Learning · Computer Science 2026-03-03 Denis Blessing , Lorenz Richter , Julius Berner , Egor Malitskiy , Gerhard Neumann

We propose and analyze new numerical methods to evaluate fractional norms and apply fractional powers of elliptic operators. By means of a reduced basis method, we project to a small dimensional subspace where explicit diagonalization via…

Numerical Analysis · Mathematics 2019-09-25 Tobias Danczul , Joachim Schöberl

With the aim of pushing the limiting magnitude of interferometric instruments, the need for wide-band detection channels and for a coordinated operation of different instruments has considerably grown in the field of long-baseline…

Instrumentation and Methods for Astrophysics · Physics 2021-09-16 Cyril Pannetier , Denis Mourard , Frédéric Cassaing , Stéphane Lagarde , Jean-Baptiste Le Bouquin , John Monnier , Judit Sturmann , Theo Ten Brummelaar

Dark-field x-ray microscopy utilizes Bragg diffraction to collect full-field x-ray images of "mesoscale" structure of ordered materials. Information regarding the structural heterogeneities and their physical implications is gleaned through…

Materials Science · Physics 2022-10-31 Omar Abulshohoud , Ishwor Poudyal , Jessica McChesney , Zhan Zhang , Zhi Qiao , Ulrich Welp , Zahir Islam

A new approach to detect change points based on differential smoothing and multiple testing is presented for long data sequences modeled as piecewise constant functions plus stationary ergodic Gaussian noise. As an application of the STEM…

Statistics Theory · Mathematics 2019-11-20 Dan Cheng , Zhibing He , Armin Schwartzman

Distributed algorithms and theories are called for in this era of big data. Under weaker local signal-to-noise ratios, we improve upon the celebrated one-round distributed principal component analysis (PCA) algorithm designed in the spirit…

Methodology · Statistics 2025-07-01 ZeYu Li , Xinsheng Zhang , Wang Zhou

In powder diffraction data analysis, phase identification is the process of determining the crystalline phases in a sample using its characteristic Bragg peaks. For multiphasic spectra, we must also determine the relative weight fraction of…

Machine Learning · Computer Science 2022-10-21 Patrick Hosein , Jaimie Greasley

In multiple change-point problems, different data segments often follow different distributions, for which the changes may occur in the mean, scale or the entire distribution from one segment to another. Without the need to know the number…

Statistics Theory · Mathematics 2014-05-29 Changliang Zou , Guosheng Yin , Long Feng , Zhaojun Wang

We consider flux-based multiple-porosity/multiple-permeability poroelasticity systems describing multiple-network flow and deformation in a poro-elastic medium, sometimes also referred to as MPET models. The focus of the paper is on the…

Numerical Analysis · Mathematics 2019-04-01 Qingguo Hong , Johannes Kraus , Maria Lymbery , Mary Fanett Wheeler

Most results in multifractal analysis are obtained using either a thermodynamic approach based on existence and uniqueness of equilibrium states or a saturation approach based on some version of the specification property. A general…

Dynamical Systems · Mathematics 2019-02-20 Vaughn Climenhaga

Multifractal analysis of multiplicative random cascades is revisited within the framework of {\em mixed asymptotics}. In this new framework, statistics are estimated over a sample which size increases as the resolution scale (or the…

Probability · Mathematics 2008-05-05 Emmanuel Bacry , Arnaud Gloter , Marc Hoffmann , Jean-Francois Muzy

The analysis of data sets arising from multiple sensors has drawn significant research attention over the years. Traditional methods, including kernel-based methods, are typically incapable of capturing nonlinear geometric structures. We…

Data Analysis, Statistics and Probability · Physics 2017-08-04 Ronen Talmon , Hau-tieng Wu

There are many different ways in which change point analysis can be performed, from purely parametric methods to those that are distribution free. The ecp package is designed to perform multiple change point analysis while making as few…

Computation · Statistics 2013-11-26 Nicholas A. James , David S. Matteson

In this article we consider static Bayesian parameter estimation for partially observed diffusions that are discretely observed. We work under the assumption that one must resort to discretizing the underlying diffusion process, for…

Computation · Statistics 2017-01-23 Ajay Jasra , Kengo Kamatani , Kody J. H. Law , Yan Zhou
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