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The Random Variable Transformation (RVT) method is a fundamental tool for determining the probability distribution function associated with a Random Variable (RV) Y=g(X), where X is a RV and g is a suitable transformation. In the usual…

Probability · Mathematics 2024-05-07 Fabrizio Masullo , Fabio Zanolin , Josep Bonet Avalos

This work brings together two powerful concepts in Gaussian processes: the variational approach to sparse approximation and the spectral representation of Gaussian processes. This gives rise to an approximation that inherits the benefits of…

Machine Learning · Statistics 2017-11-09 James Hensman , Nicolas Durrande , Arno Solin

We revisit the replica method for analyzing inference and learning in parametric models, considering situations where the data-generating distribution is unknown or analytically intractable. Instead of assuming idealized distributions to…

Disordered Systems and Neural Networks · Physics 2025-11-17 Takashi Takahashi

The paper considers so-called adaptive estimations of regression, distribution density and spectral density of a Gaussian stationary sequence, asymptotically optimal in order at a growing number of observation on any regular subspace…

Probability · Mathematics 2007-05-23 Eugene Ostrovsky , Leonid Sirota

In this article we propose a new adaptive numerical quadrature procedure which includes both local subdivision of the integration domain, as well as local variation of the number of quadrature points employed on each subinterval. In this…

Numerical Analysis · Mathematics 2015-08-17 Paul Houston , Thomas P. Wihler

We present a method for the numerical computation of Fourier-Bessel transforms on a finite or infinite interval. The function to be transformed needs to be evaluated on a grid of points that is independent of the argument of the Bessel…

High Energy Physics - Phenomenology · Physics 2024-08-21 Markus Diehl , Oskar Grocholski

Inference for GP models with non-Gaussian noises is computationally expensive when dealing with large datasets. Many recent inference methods approximate the posterior distribution with a simpler distribution defined on a small number of…

Machine Learning · Computer Science 2018-09-11 Linfeng Liu , Liping Liu

Graph-based models require aggregating information in the graph from neighbourhoods of different sizes. In particular, when the data exhibit varying levels of smoothness on the graph, a multi-scale approach is required to capture the…

Machine Learning · Computer Science 2022-02-22 Felix L. Opolka , Yin-Cong Zhi , Pietro Liò , Xiaowen Dong

We treat the quaternionic Fourier transform (QFT) applied to quaternion fields and investigate QFT properties useful for applications. Different forms of the QFT lead us to different Plancherel theorems. We relate the QFT computation for…

Rings and Algebras · Mathematics 2013-06-06 Eckhard Hitzer

We present a simple scheme to evaluate linear response functions including quantum fluctuation corrections on top of the Gutzwiller approximation. The method is derived for a generic multi-band lattice Hamiltonian without any assumption…

Strongly Correlated Electrons · Physics 2017-03-08 Michele Fabrizio

In this paper, we discuss vector-valued Gaussian processes for the approximation of divergence- or rotation-free functions. We establish the theory for such Gaussian processes, then link the theory to multivariate approximation theory, and…

Numerical Analysis · Mathematics 2025-11-18 Quoc Thong Le Gia , Ian Hugh Sloan , Holger Wendland

This paper investigates the statistical properties of non-linear transformations (NLT) of random variables, in order to establish useful tools for estimation and information theory. Specifically, the paper focuses on linear regression…

Information Theory · Computer Science 2013-05-13 Paolo Banelli

The dynamics of a one-dimensional stochastic model is studied in presence of an absorbing boundary. The distribution of fluctuations is analytically characterized within the generalized van Kampen expansion, accounting for higher order…

Statistical Mechanics · Physics 2015-05-28 Claudia Cianci , Francesca Di Patti , Duccio Fanelli

We investigate the complex Gaussian as well as non-Gaussian distributed random analytical and entire functions (complex entire random field) and calculate their domain of definiteness (radius of convergence) as well as some important…

Complex Variables · Mathematics 2020-11-03 Maria Rosaria Formica , Eugeny Ostrovsky , Leonid Sirota

A distributional route to Gaussianity, associated with the concept of Conservative Mixing Transformations in ensembles of random vector-valued variables, is proposed. This route is completely different from the additive mechanism…

Statistical Mechanics · Physics 2023-01-11 Massimiliano Giona , Chiara Pezzotti , Giuseppe Procopio

Gaussian distributions can be generalized from Euclidean space to a wide class of Riemannian manifolds. Gaussian distributions on manifolds are harder to make use of in applications since the normalisation factors, which we will refer to as…

Probability · Mathematics 2023-02-16 Simon Heuveline , Salem Said , Cyrus Mostajeran

Computation of moments of transformed random variables is a problem appearing in many engineering applications. The current methods for moment transformation are mostly based on the classical quadrature rules which cannot account for the…

Methodology · Statistics 2017-01-06 Jakub Prüher , Ondřej Straka

Modeling spectral line profiles taking frequency redistribution effects into account is a notoriously challenging problem from the computational point of view, especially when polarization phenomena (atomic polarization and polarized…

Solar and Stellar Astrophysics · Physics 2021-01-04 A. Paganini , B. Hashemi , E. Alsina Ballester , L. Belluzzi

In the present article the author extends the Fourier transform to a more general class of functions; First to power-law functions with integer and half-integer exponents then to the widely used quantum statistics function (Fermi-Dirac and…

General Mathematics · Mathematics 2019-12-30 Cyril Belardinelli

Distribution functions for random variables that depend on a parameter are computed asymptotically for ensembles of positive Hermitian matrices. The inverse Fourier transform of the distribution is shown to be a Fredholm determinant of a…

Functional Analysis · Mathematics 2009-11-07 Estelle L. Basor