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Estimation of the complete distribution of a random variable is a useful primitive for both manual and automated decision making. This problem has received extensive attention in the i.i.d. setting, but the arbitrary data dependent setting…

Machine Learning · Statistics 2023-03-01 Paul Mineiro , Steven R. Howard

We establish new constraints on $f(T)$ gravity models by using cosmological data. In particular, we investigate the restrictions given by the gas mass fraction measurements of galaxy clusters and transversal BAO data. Both data sets are…

Cosmology and Nongalactic Astrophysics · Physics 2022-09-28 F. B. M. dos Santos , J. E. Gonzalez , R. Silva

In this paper, I derive the limiting behaviour of the solutions to Poisson's equation, in a perforated domain, subject to inhomogeneous Robin boundary conditions. In the first half of the paper, I derive a generalised limit for non-periodic…

Analysis of PDEs · Mathematics 2022-10-04 Aaron Pim

The sensitivity parameter is widely used for quantifying fine tuning. However, examples show it fails to give correct results under certain circumstances. We argue that these problems only occur when calculating the sensitivity of a…

High Energy Physics - Phenomenology · Physics 2007-10-24 Su Yan

Shape restrictions have played a central role in economics as both testable implications of theory and sufficient conditions for obtaining informative counterfactual predictions. In this paper we provide a general procedure for inference…

Statistics Theory · Mathematics 2022-04-29 Victor Chernozhukov , Whitney K. Newey , Andres Santos

Constrained generative modeling is fundamental to applications such as robotic control and autonomous driving, where models must respect physical laws and safety-critical constraints. In real-world settings, these constraints rarely take…

Machine Learning · Computer Science 2026-03-10 Xiaoxuan Liang , Saeid Naderiparizi , Yunpeng Liu , Berend Zwartsenberg , Frank Wood

Correlations between factors of variation are prevalent in real-world data. Exploiting such correlations may increase predictive performance on noisy data; however, often correlations are not robust (e.g., they may change between domains,…

Machine Learning · Computer Science 2022-12-26 Christina M. Funke , Paul Vicol , Kuan-Chieh Wang , Matthias Kümmerer , Richard Zemel , Matthias Bethge

Researchers develop models to explain the unknowns. These models typically involve parameters that capture tangible quantities, the estimation of which is desired. Parameter identifiability investigates the recoverability of the unknown…

Optimization and Control · Mathematics 2024-07-01 Anuththara Sarathchandra , Azadeh Aghaeeyan , Pouria Ramazi

Conditional independence and graphical models are well studied for probability distributions on product spaces. We propose a new notion of conditional independence for any measure $\Lambda$ on the punctured Euclidean space $\mathbb…

Statistics Theory · Mathematics 2024-09-12 Sebastian Engelke , Jevgenijs Ivanovs , Kirstin Strokorb

A generic physical situation is considered where Im $\Pi$, the imaginary part of polarization operator (generalized susceptibility), can be measured on a finite interval and the high frequency asymptotics (up to a few orders) of $\Pi$ can…

High Energy Physics - Phenomenology · Physics 2007-05-23 Alexander Moroz , Jan Fischer

Real-world time series data are often generated from several sources of variation. Learning representations that capture the factors contributing to this variability enables a better understanding of the data via its underlying generative…

Machine Learning · Computer Science 2022-02-14 Sana Tonekaboni , Chun-Liang Li , Sercan Arik , Anna Goldenberg , Tomas Pfister

Dynamic Complexity studies the maintainability of queries with logical formulas in a setting where the underlying structure or database changes over time. Most often, these formulas are from first-order logic, giving rise to the dynamic…

Logic in Computer Science · Computer Science 2019-10-16 Jonas Schmidt , Thomas Schwentick , Nils Vortmeier , Thomas Zeume , Ioannis Kokkinis

We study the problem of distance-based formation control in autonomous multi-agent systems in which only distance measurements are available. This means that the target formations as well as the sensed variables are both determined by…

Dynamical Systems · Mathematics 2018-06-28 Raik Suttner , Zhiyong Sun

We analyze a homogenization limit for the linear wave equation of second order. The spatial operator is assumed to be of divergence form with an oscillatory coefficient matrix $a^\varepsilon$ that is periodic with characteristic length…

Analysis of PDEs · Mathematics 2014-01-31 Tomas Dohnal , Agnes Lamacz , Ben Schweizer

We describe in great generality features concerning constrained entropic, functional variational problems that allow for a broad range of applications. Our discussion encompasses not only entropies but, potentially, any functional of the…

Statistical Mechanics · Physics 2018-08-22 A. R. Plastino , A. Plastino , M. C. Rocca

High-dimensional limit theorems have been shown useful to derive tuning rules for finding the optimal scaling in random-walk Metropolis algorithms. The assumptions under which weak convergence results are proved are however restrictive: the…

Methodology · Statistics 2022-02-16 Sebastian M Schmon , Philippe Gagnon

In this paper we propose a solution to the problem of parameter estimation of nonlinearly parameterized regressions--continuous or discrete time--and apply it for system identification and adaptive control. We restrict our attention to…

Optimization and Control · Mathematics 2019-10-18 Romeo Ortega , Vladislav Gromov , Emmanuel Nuño , Anton Pyrkin , Jose Guadalupe Romero

There are several studies proposing phenomenological consequences of a deformation of special and general relativity. Here, we cast novel constraints on the deformation parameter of a metric in the cotangent bundle accounting for a curved…

General Relativity and Quantum Cosmology · Physics 2020-11-18 J. J. Relancio , S. Liberati

We introduce a new parameterization of $B\rightarrow D \pi \ell \nu$ form factors using a partial-wave expansion and derive bounds on the series coefficients using analyticity and unitarity. This is the first generalization of the…

High Energy Physics - Phenomenology · Physics 2024-10-22 Erik J. Gustafson , Florian Herren , Ruth S. Van de Water , Raynette van Tonder , Michael L. Wagman

We propose a new class of extreme-value copulas which are extreme-value limits of conditional normal models. Conditional normal models are generalizations of conditional independence models, where the dependence among observed variables is…

Methodology · Statistics 2021-02-16 Pavel Krupskii , Marc G. Genton
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