English
Related papers

Related papers: Generalized operator-scaling random ball model

200 papers

The theory of random sets is demonstrated to prove useful for the theory of random operators. A random operator is here defined by requiring the graph to be a random set. It is proved that the spectrum and the set of eigenvalues of random…

Probability · Mathematics 2019-09-16 Gunnar Taraldsen

A general random effects model is proposed that allows for continuous as well as discrete distributions of the responses. Responses can be unrestricted continuous, bounded continuous, binary, ordered categorical or given in the form of…

Methodology · Statistics 2024-04-30 Gerhard Tutz

Symbolic regression algorithms search a space of mathematical expressions for formulas that explain given data. Transformer-based models have emerged as a promising, scalable approach shifting the expensive combinatorial search to a…

Machine Learning · Computer Science 2025-09-25 Henrik Voigt , Paul Kahlmeyer , Kai Lawonn , Michael Habeck , Joachim Giesen

In this paper we generalize the Ball-Collision Algorithm by Bernstein, Lange, Peters from the binary field to a general finite field. We also provide a complexity analysis and compare the asymptotic complexity to other generalized…

Information Theory · Computer Science 2018-12-31 Carmelo Interlando , Karan Khathuria , Nicole Rohrer , Joachim Rosenthal , Violetta Weger

We present a brief introduction to the theory of operator limits of random matrices to non-experts. Several open problems and conjectures are given. Connections to statistics, integrable systems, orthogonal polynomials, and more, are…

Probability · Mathematics 2018-08-31 Balint Virag

A flexible model is developed for multivariate generalized spherical distributions, i.e. ones with level sets that are star shaped. To work in dimension above 2 requires tools from computational geometry and multivariate numerical…

Computation · Statistics 2015-10-26 John P Nolan

Probabilistic diffusion models enjoy increasing popularity in the deep learning community. They generate convincing samples from a learned distribution of input images with a wide field of practical applications. Originally, these…

Image and Video Processing · Electrical Eng. & Systems 2023-09-19 Pascal Peter

Divergence-form operators with random coefficients homogenize over large scales. Over the last decade, an intensive research effort focused on turning this asymptotic statement into quantitative estimates. The goal of this note is to review…

Mathematical Physics · Physics 2019-05-01 Jean-Christophe Mourrat

We introduce and study the generalized Wigner operator. By definition, such an operator transforms the Wigner wave function into a local relativistic field corresponding to an irreducible representation of the Poincar\'e group by extended…

High Energy Physics - Theory · Physics 2023-04-13 I. L. Buchbinder , A. P. Isaev , M. A. Podoinitsyn , S. A. Fedoruk

In the study of natural and artificial complex systems, responses that are not completely determined by the considered decision variables are commonly modelled probabilistically, resulting in response distributions varying across decision…

Methodology · Statistics 2021-10-07 Athénaïs Gautier , David Ginsbourger , Guillaume Pirot

A general stochastic approach to the description of coagulating aerosol system is developed. As the object of description one can consider arbitrary mesoscopic values (number of aerosol clusters, their size etc). The birth-and-death…

Chemical Physics · Physics 2011-10-12 V. V. Ryazanov

The convergence of a new general variable metric algorithm based on compositions of averaged operators is established. Applications to monotone operator splitting are presented.

Optimization and Control · Mathematics 2018-07-12 Lilian E. Glaudin

In the article we propose a general scheme for solutions of some approximation problems under a rather general setting. We illustrate the application of the proposed scheme by a series of examples, in particular we show that many results in…

Functional Analysis · Mathematics 2023-12-29 Oleg Kovalenko

A flexible model for non-stationary Gaussian random fields on hypersurfaces is introduced.The class of random fields on curves and surfaces is characterized by an amplitude spectral density of a second order elliptic differential…

Numerical Analysis · Mathematics 2024-12-02 Erik Jansson , Annika Lang , Mike Pereira

This paper studies a very general urn model stimulated by designs in clinical trials, where the number of balls of different types added to the urn at trial n depends on a random outcome directed by the composition at trials 1,2,...,n-1.…

Probability · Mathematics 2007-05-23 Zhi-Dong Bai , Feifang Hu

Using a scheme involving a lifting of a row contraction we introduce a toy model of repeated interactions between quantum systems. In this model there is an outgoing Cuntz scattering system involving two wandering subspaces. We associate to…

Operator Algebras · Mathematics 2014-03-18 Santanu Dey , Kalpesh J. Haria

Ideas and results of the generalized wave operator theory for dynamical and stationary cases are developed further and exact expressions for generalized scattering operators are obtained for wide classes of differential equations. New…

Mathematical Physics · Physics 2016-02-24 Lev Sakhnovich

Two classes of multivariate random fields with operator-stable marginals are constructed. The random fields $\mathbb{X}=\{X(t) : t \in \mathbb{R}^d \}$ with values in $\mathbb{R}^m$ are invariant in law under operator-scaling in both the…

Probability · Mathematics 2017-12-15 Dustin Kremer , Hans-Peter Scheffler

This paper introduces a new generalization of the power generalized Weibull distribution called the generalized power generalized Weibull distribution. This distribution can also be considered as a generalization of Weibull distribution.…

Statistics Theory · Mathematics 2018-10-16 Mahmoud Ali Selim

We propose a new modeling approach that is a generalization of generative and discriminative models. The core idea is to use an implicit parameterization of a joint probability distribution by specifying only the conditional distributions.…

Machine Learning · Computer Science 2016-12-06 Dmitrij Schlesinger , Carsten Rother