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The paper treats density measures as typical examples of finitely additive measures in $\mathbb{R}^n$. We study their structure and derive basic properties. In addition, estimates for related integrals are provided. The results are applied…

Analysis of PDEs · Mathematics 2026-03-26 Moritz Schönherr , Friedemann Schuricht

We study the asymptotic convergence of the partial averaging method, a technique used in conjunction with the random series implementation of the Feynman-Kac formula. We prove asymptotic bounds valid for most series representations in the…

Statistical Mechanics · Physics 2007-05-23 Cristian Predescu , J. D. Doll , David L. Freeman

We provide a probabilistic representation for the derivative of the semigroup corresponding to a diffusion process killed at the boundary of a half interval. In particular, we show that the derivative of the semi-group can be expressed as…

Probability · Mathematics 2024-06-10 Dan Crisan , Arturo Kohatsu-Higa

We derive a residual based a-posteriori error estimate for the outer normal flux of approximations to {the diffusion problem with variable coefficient}. By analyzing the solution of the adjoint problem, we show that error indicators in the…

Numerical Analysis · Mathematics 2021-10-26 Silvia Bertoluzza , Erik Burman , Cuiyu He

The incompressible limit of nonlinear diffusion equations of porous medium type has attracted a lot of attention in recent years, due to its ability to link the weak formulation of cell-population models to free boundary problems of…

Analysis of PDEs · Mathematics 2021-08-03 Noemi David , Tomasz Dębiec , Benoît Perthame

In the paper, the basic results on boundary trace of the book "Sobolev spaces" by V. Maz'ya are generalized to a wider class of regions. In the book, boundary trace of BV-functions is defined for regions with finite perimeter and the main…

Functional Analysis · Mathematics 2009-03-27 Yuri Burago , Nikolay Kosovskiy

Describing particle transport at the macroscopic or mesoscopic level in non-ideal environments poses fundamental theoretical challenges in domains ranging from inter and intra-cellular transport in biology to diffusion in porous media. Yet,…

Statistical Mechanics · Physics 2013-09-11 Marta Galanti , Duccio Fanelli , Francesco Piazza

In this article, we introduce mixture representations for likelihood ratio ordered distributions. Essentially, the ratio of two probability densities, or mass functions, is monotone if and only if one can be expressed as a mixture of…

Methodology · Statistics 2023-10-30 Michael Jauch , Andrés F. Barrientos , Víctor Peña , David S. Matteson

Compositional data, representing proportions constrained to the simplex, arise in diverse fields such as geosciences, ecology, genomics, and microbiome research. Existing nonparametric density estimation methods often rely on…

Methodology · Statistics 2025-10-10 Jiajin Xie , Yong Wang , Eduardo García-Portugués

Nonparametric density estimators are studied for $d$-dimensional, strongly spatial mixing data which is defined on a general $N$-dimensional lattice structure. We consider linear and nonlinear hard thresholded wavelet estimators which are…

Statistics Theory · Mathematics 2017-12-27 Johannes T. N. Krebs

Divergence estimators based on direct approximation of density-ratios without going through separate approximation of numerator and denominator densities have been successfully applied to machine learning tasks that involve distribution…

Machine Learning · Statistics 2011-06-24 Makoto Yamada , Taiji Suzuki , Takafumi Kanamori , Hirotaka Hachiya , Masashi Sugiyama

Consider the Boltzmann equation in a general non-convex domain with the diffuse boundary condition. We establish optimal BV estimates for such solutions. Our method consists of a new $W^{1,1}-$trace estimate for the diffuse boundary…

Analysis of PDEs · Mathematics 2018-09-11 Yan Guo , Chanwoo Kim , Daniela Tonon , Ariane Trescases

The paper introduces a new estimation method for the standard linear regression model. The procedure is not driven by the optimisation of any objective function rather, it is a simple weighted average of slopes from observation pairs. The…

Econometrics · Economics 2024-02-27 Felix Chan , Laszlo Matyas

The Dirichlet form is a generalization of the Laplacian, heavily used in the study of many diffusion-like processes. In this paper we present a nonstandard representation theorem for the Dirichlet form, showing that the usual Dirichlet form…

Probability · Mathematics 2020-10-07 Robert M. Anderson , Haosui Duanmu , Aaron Smith

Variational representations of divergences and distances between high-dimensional probability distributions offer significant theoretical insights and practical advantages in numerous research areas. Recently, they have gained popularity in…

Machine Learning · Computer Science 2022-03-25 Jeremiah Birrell , Markos A. Katsoulakis , Yannis Pantazis

This invited paper proposes and discusses several Bayesian attempts at nonparametric and semiparametric density estimation. The main categories of these ideas are as follows: 1) Build a nonparametric prior around a given parametric model.…

Statistics Theory · Mathematics 2026-04-23 Nils Lid Hjort

We introduced a new continued fraction expansions in our previous paper. For these expansions, we show formulae of probability about incomplete quotients. Furthermore, we prove the existence of invariant measures with respect to the…

Number Theory · Mathematics 2010-11-24 Dan Lascu , Katsunori Kawamura

We establish a relation between the approximation in $L^2[-\pi,\pi]$ by exponentials with the set of frequencies of Beurling--Malliavin density less than $1$ and the meromorphic interpolation at $\mathbb Z$. Furthermore, we show that…

Complex Variables · Mathematics 2025-04-28 Yurii Belov , Alexander Borichev , Alexander Kuznetsov

This paper is devoted to the approximation of the linear Boltzmann equation by fractional diffusion equations. Most existing results address this question when there is no external acceleration field. The goal of this paper is to…

Analysis of PDEs · Mathematics 2016-06-06 Pedro Aceves-Sanchez , Antoine Mellet

To evaluate disentangled representations several metrics have been proposed. However, theoretical guarantees for conventional metrics of disentanglement are missing. Moreover, conventional metrics do not have a consistent correlation with…

Machine Learning · Computer Science 2021-03-25 Anna Sepliarskaia , Julia Kiseleva , Maarten de Rijke