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We analyze integral representation and $\Gamma$-convergence properties of functionals defined on \emph{piecewise rigid functions}, i.e., functions which are piecewise affine on a Caccioppoli partition where the derivative in each component…

Analysis of PDEs · Mathematics 2020-02-04 Manuel Friedrich , Francesco Solombrino

An approach to generalize any kind of collinear functionals in density functional theory to non-collinear functionals is proposed. This approach, for the very first time, satisfies the correct collinear limit for any kind of functionals,…

Quantum Physics · Physics 2023-01-26 Zhichen Pu , Hao Li , Qiming Sun , Ning Zhang , Yong Zhang , Sihong Shao , Hong Jiang , Yiqin Gao , Yunlong Xiao

This article investigates nonparametric estimation of variance functions for functional data when the mean function is unknown. We obtain asymptotic results for the kernel estimator based on squared residuals. Similar to the finite…

Methodology · Statistics 2008-12-16 Heng Lian

Description of linear continuous functionals on a space of rapidly decreasing infinitely differentiable functions on an unbounded closed convex set in $\mathbb R^n$ in terms of their Fourier-Laplace transform is obtained.

Complex Variables · Mathematics 2010-03-18 I. Kh. Musin , P. V. Yakovleva

Functional data that are nonnegative and have a constrained integral can be considered as samples of one-dimensional density functions. Such data are ubiquitous. Due to the inherent constraints, densities do not live in a vector space and,…

Statistics Theory · Mathematics 2016-01-13 Alexander Petersen , Hans-Georg Müller

Usually, the dynamics of linear time-invariant systems described by an integral operator of convolution type, which is defined in the Hilbert space of Lebesgue square integrable functions on the whole line. Such a description leads to…

Systems and Control · Computer Science 2012-01-18 V. N. Tibabishev

Analyticity results of expected pressure and invariant densities in the context of random dynamics of transcendental functions are established. These are obtained by a refinement of work by Rugh leading to a simple approach to analyticity.…

Dynamical Systems · Mathematics 2020-02-19 Volker Mayer , Mariusz Urbanski , Anna Zdunik

Various approaches to stochastic processes exist, noting that key properties such as measurability and continuity are not trivially satisfied. We introduce a new theory for Gaussian processes using improper linear functionals. Using a…

Statistics Theory · Mathematics 2020-10-15 Niels Lundtorp Olsen

Finite temperature density functional theory requires representations for the internal energy, entropy, and free energy as functionals of the local density field. A central formal difficulty for an orbital-free representation is…

Statistical Mechanics · Physics 2011-05-12 James W. Dufty , S. B. Trickey

We study functional stochastic differential equations with a locally unbounded, functional drift focusing on well-posedness, stability and the strong Feller property. Following the non-functional case, we only consider integrability…

Probability · Mathematics 2020-09-08 Stefan Bachmann

In this paper we study the asymptotic behaviour via Gamma-convergence of some integral functionals which model some multi-dimensional structures and depend explicitly on the linearized strain tensor. The functionals are defined in…

Functional Analysis · Mathematics 2007-05-23 Nadia Ansini , Francois Bille Ebobisse

We propose finitely convergent methods for solving convex feasibility problems defined over a possibly infinite pool of constraints. Following other works in this area, we assume that the interior of the solution set is nonempty and that…

Optimization and Control · Mathematics 2020-09-22 Victor I. Kolobov , Simeon Reich , Rafał Zalas

We give extensional and intensional characterizations of functional programs with nondeterminism: as structure preserving functions between biorders, and as nondeterministic sequential algorithms on ordered concrete data structures which…

Logic in Computer Science · Computer Science 2023-06-22 James Laird

Information functionals allow to quantify the degree of randomness of a given probability distribution, either absolutely (through min/max entropy principles) or relative to a prescribed reference one. Our primary aim is to analyze the…

Quantum Physics · Physics 2007-11-22 Piotr Garbaczewski

This work presents the general form solution of Koopman Partial Differential Equation and shows that its functional dimensionality is finite. The dimensionality is as the dimensionality of the dynamics. Thus, the representation of nonlinear…

Analysis of PDEs · Mathematics 2024-01-05 Ido Cohen , Eli Appleboim , Gershon Wolansky

In this paper we prove that an operator which projects weak solutions of the two- or three-dimensional Navier-Stokes equations onto a finite-dimensional space is determining if it annihilates the difference of two "nearby" weak solutions…

Analysis of PDEs · Mathematics 2010-01-12 Michael Holst , Edriss Titi

We can, and should, do statistical inference on simulation models by adjusting the parameters in the simulation so that the values of {\em randomly chosen} functions of the simulation output match the values of those same functions…

Methodology · Statistics 2021-11-18 Cosma Rohilla Shalizi

We prove that certain quotients of entire functions are characteristic functions. Under some conditions, the probability measure corresponding to a characteristic function of that type has a density which can be expressed as a generalized…

Probability · Mathematics 2010-09-09 Albert Ferreiro-Castilla , Frederic Utzet

Potential functionals have been introduced recently as an important tool for the analysis of coupled scalar systems (e.g. density evolution equations). In this contribution, we investigate interesting properties of this potential. Using the…

Information Theory · Computer Science 2017-01-16 Rafah El-Khatib , Nicolas Macris , Tom Richardson , Rüdiger Urbanke

Diffusion models are a class of probabilistic generative models that have been widely used as a prior for image processing tasks like text conditional generation and inpainting. We demonstrate that these models can be adapted to make…

Machine Learning · Computer Science 2023-06-14 Marc Finzi , Anudhyan Boral , Andrew Gordon Wilson , Fei Sha , Leonardo Zepeda-Núñez
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