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This work aims to extend the existing results on thick points of logarithmic-correlated Gaussian Free Fields to Gaussian random fields that are more singular. To be specific, we adopt a sphere averaging regularization to study…

Probability · Mathematics 2015-12-23 Linan Chen

Massive and massless Gaussian free fields can be described as generalized Gaussian processes indexed by an appropriate space of functions. In this article we study various approaches to approximate these fields and look at the fractal…

Probability · Mathematics 2015-02-11 Alessandra Cipriani , Rajat Subhra Hazra

Fine regularity of stochastic processes is usually measured in a local way by local H\"older exponents and in a global way by fractal dimensions. Following a previous work of Adler, we connect these two concepts for multiparameter Gaussian…

Probability · Mathematics 2012-06-05 Erick Herbin , Benjamin Arras , Geoffroy Barruel

This article is concerned with the study of the fractal dimension of thick points for a 4-dimensional Gaussian Free Field. We adopt the definition of Gaussian Free Field on $\R^4$ introduced by Chen and Jakobson (2012) viewed as an abstract…

Probability · Mathematics 2014-05-08 Alessandra Cipriani , Rajat Subhra Hazra

Dimensions of level sets of generic continuous functions and generic H\"older functions defined on a fractal $F$ encode information about the geometry, ``the thickness" of $F$. While in the continuous case this quantity is related to a…

Classical Analysis and ODEs · Mathematics 2024-10-10 Zoltán Buczolich , Balázs Maga , Gáspár Vértesy

We develop a method to evaluate the generalized degrees of freedom (GDF), which is a key quantity of a model selection criterion, for linear regression with sparse regularization. Using the replica method, GDF is expressed by the variables…

Information Theory · Computer Science 2017-01-04 Ayaka Sakata

In this paper, we study the Hausdorff dimension of self-similar measures and sets on the real line, where the generating iterated function system consists of some maps that share the same fixed point. In particular, we will show that out of…

Dynamical Systems · Mathematics 2025-07-09 Balázs Bárány , Manuj Verma

We consider the maximum of the discrete two dimensional Gaussian free field (GFF) in a box, and prove that its maximum, centered at its mean, is tight, settling a long-standing conjecture. The proof combines a recent observation of…

Probability · Mathematics 2010-09-20 Maury Bramson , Ofer Zeitouni

Let $U\subseteq\mathbf{C}$ be a bounded domain with smooth boundary and let $F$ be an instance of the continuum Gaussian free field on $U$ with respect to the Dirichlet inner product $\int_U\nabla f(x)\cdot \nabla g(x)\,dx$. The set…

Probability · Mathematics 2010-10-05 Xiaoyu Hu , Jason Miller , Yuval Peres

Smart training set selections procedures enable the reduction of data needs and improves predictive robustness in machine learning problems relevant to chemistry. We introduce Gradient Guided Furthest Point Sampling (GGFPS), a simple…

Machine Learning · Statistics 2025-10-13 Morris Trestman , Stefan Gugler , Felix A. Faber , O. A. von Lilienfeld

The Gaussian Free Field (GFF) is a canonical random surface in probability theory generalizing Brownian motion to higher dimensions. In two dimensions, it is critical in several senses, and is expected to be the universal scaling limit of a…

Probability · Mathematics 2023-02-28 Shirshendu Ganguly , Reza Gheissari

We establish a rigorous asymptotic theory for the joint estimation of roughness and scale parameters in two-dimensional Gaussian random fields with power-law generalized covariances \cite{Matheron1973, Stein1999, Yaglom1987}. Our main…

Statistics Theory · Mathematics 2025-10-31 Varun Kotharkar , Michael L. Stein

In this paper, we study a random field constructed from the two-dimensional Gaussian free field (GFF) by modifying the variance along the scales in the neighborhood of each point. The construction can be seen as a local martingale transform…

Probability · Mathematics 2022-05-25 Louis-Pierre Arguin , Frédéric Ouimet

We consider the family of CIFSs of generalized complex continued fractions with a complex parameter space. This is a new interesting example to which we can apply a general theory of infinite CIFSs and analytic families of infinite CIFSs.…

Dynamical Systems · Mathematics 2020-02-27 Kanji Inui , Hikaru Okada , Hiroki Sumi

Studying sample path behaviour of stochastic fields/processes is a classical research topic in probability theory and related areas such as fractal geometry. To this end, many methods have been developed since a long time in Gaussian…

Probability · Mathematics 2016-06-13 Antoine Ayache , Geoffrey Boutard

We consider the discrete Gaussian Free Field (DGFF) in scaled-up (square-lattice) versions of suitably regular continuum domains $D\subset\mathbb C$ and describe the scaling limit, including local structure, of the level sets at heights…

Probability · Mathematics 2020-01-06 Marek Biskup , Oren Louidor

Let $g_0$ be a smooth pinched negatively curved Riemannian metric on a complete surface $N$, and let $\Lambda_0$ be a basic hyperbolic set of the geodesic flow of $g_0$ with Hausdorff dimension strictly smaller than two. Given a small…

Dynamical Systems · Mathematics 2018-06-11 A. Cerqueira , C. G. Moreira , S. Romaña

This paper examines level sets of two families of continuous, nowhere differentiable functions (one a subfamily of the other) defined in terms of the "tent map". The well-known Takagi function is a special case. Sharp upper bounds are given…

Classical Analysis and ODEs · Mathematics 2019-02-20 Pieter C. Allaart

Hausdorff dimensions of level sets of generic continuous functions defined on fractals can give information about the "thickness/narrow cross-sections'' of a "network" corresponding to a fractal set, $F$. This lead to the definition of the…

Classical Analysis and ODEs · Mathematics 2022-10-05 Zoltán Buczolich , Balázs Maga , Gáspár Vértesy

Let us assume that $f$ is a continuous function defined on the unit ball of $\mathbb R^d$, of the form $f(x) = g (A x)$, where $A$ is a $k \times d$ matrix and $g$ is a function of $k$ variables for $k \ll d$. We are given a budget $m \in…

Numerical Analysis · Mathematics 2012-01-18 Massimo Fornasier , Karin Schnass , Jan Vybiral
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