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Related papers: Generalized stochastic processes revisited

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We study random graphs with latent geometric structure, where the probability of each edge depends on the underlying random positions corresponding to the two endpoints. We focus on the setting where this conditional probability is a…

Probability · Mathematics 2021-11-01 Suqi Liu , Miklos Z. Racz

A real quadratic matrix is generalized doubly stochastic (g.d.s.) if all of its row sums and column sums equal one. We propose numerically stable methods for generating such matrices having possibly orthogonality property or/and satisfying…

Numerical Analysis · Computer Science 2018-09-21 Gianluca Oderda , Alicja Smoktunowicz , Ryszard Kozera

We consider positive, integral-preserving linear operators acting on $L^1$ space, known as stochastic operators or Markov operators. We show that, on finite-dimensional spaces, any stochastic operator can be approximated by a sequence of…

Functional Analysis · Mathematics 2019-06-13 Shirin Moein , Rajesh Pereira , Sarah Plosker

A central question in rough path theory is characterising the law of stochastic processes on path spaces. It is established in [I. Chevyrev & T. Lyons, Characteristic functions of measures on geometric rough paths, Ann. Probab. 44 (2016),…

Probability · Mathematics 2025-08-26 Siran Li , Zijiu Lyu , Hao Ni , Jiajie Tao

The relation between continuous functions and random vectors is revealed in the paper that the main meaning is described as, for any given continuous function, there must be a sequence of probability spaces and a sequence of random vectors…

Probability · Mathematics 2022-11-15 Hong-Xing Li , Wei Zhou , Hong-Hai Mi

We introduce and analyze spaces and algebras of generalized functions which correspond to H\" older, Zygmund, and Sobolev spaces of functions. The main scope of the paper is the characterization of the regularity of distributions that are…

Functional Analysis · Mathematics 2013-05-02 Stevan Pilipović , Dimitris Scarpalezos , Jasson Vindas

We establish well-posedness and maximal regularity estimates for linear parabolic SPDE in divergence form involving random coefficients that are merely bounded and measurable in the time, space, and probability variables. To reach this…

Analysis of PDEs · Mathematics 2023-10-17 Pascal Auscher , Pierre Portal

We consider several notions of regularity, including strong regularity, bounded relative units, and Ditkin's condition, in the setting of vector-valued function algebras. Given a commutative Banach algebra $A$ and a compact space $X$, let…

Functional Analysis · Mathematics 2023-02-16 Z. Barqi , M. Abtahi

We investigate the random dynamics of rational maps on the Riemann sphere and the dynamics of semigroups of rational maps on the Riemann sphere. We show that regarding random complex dynamics of polynomials, in most cases, the chaos of the…

Dynamical Systems · Mathematics 2014-02-26 Hiroki Sumi

In this work we consider infinite dimensional extensions of some finite dimensional Gaussian geometric functionals called the Gaussian Minkowski functionals. These functionals appear as coefficients in the probability content of a tube…

Probability · Mathematics 2013-07-26 Jonathan E. Taylor , Sreekar Vadlamani

We raise the following general question regarding a ring graded by a group: "If $P$ is a ring-theoretic property, how does one define the graded version $P_{\operatorname{gr}}$ of the property $P$ in a meaningful way?". Some properties of…

Rings and Algebras · Mathematics 2023-12-05 Lia Vas

Given a c\`adl\`ag process $X$ on a filtered measurable space, we construct a version of its semimartingale characteristics which is measurable with respect to the underlying probability law. More precisely, let $\mathfrak{P}_{sem}$ be the…

Probability · Mathematics 2014-07-08 Ariel Neufeld , Marcel Nutz

We investigate the connections between the mean pathwise regularity of stochastic processes and their L^r(P)-functional quantization rates as random variables taking values in some L^p([0,T],dt)-spaces (0 < p <= r). Our main tool is the…

Probability · Mathematics 2013-04-03 Harald Luschgy , Gilles Pagès

Treating neural network inputs and outputs as random variables, we characterize the structure of neural networks that can be used to model data that are invariant or equivariant under the action of a compact group. Much recent research has…

Machine Learning · Statistics 2020-09-18 Benjamin Bloem-Reddy , Yee Whye Teh

Standard geostatistical models assume second order stationarity of the underlying Random Function. In some instances, there is little reason to expect the spatial dependence structure to be stationary over the whole region of interest. In…

Methodology · Statistics 2014-12-04 Francky Fouedjio , Nicolas Desassis , Jacques Rivoirard

The paper is devoted to a comprehensive second-order study of a remarkable class of convex extended-real-valued functions that is highly important in many aspects of nonlinear and variational analysis, specifically those related to…

Optimization and Control · Mathematics 2015-07-21 Boris S. Mordukhovich , M. Ebrahim Sarabi

We consider random iteration of exponential entire functions, i.e. of the form ${\mathbb C}\ni z\mapsto f_\lambda(z):=\lambda e^z\in\mathbb C$, $\lambda\in{\mathbb C}\setminus \{0\}$. Assuming that $\lambda$ is in a bounded closed interval…

Dynamical Systems · Mathematics 2018-05-22 Mariusz Urbański , Anna Zdunik

We study the convergence of random function iterations for finding an invariant measure of the corresponding Markov operator. We call the problem of finding such an invariant measure the stochastic fixed point problem. This generalizes…

Functional Analysis · Mathematics 2022-03-24 Neal Hermer , D. Russell Luke , Anja Sturm

We consider a product of an arbitrary number of independent rectangular Gaussian random matrices. We derive the mean densities of its eigenvalues and singular values in the thermodynamic limit, eventually verified numerically. These…

Statistical Mechanics · Physics 2011-06-28 Z. Burda , A. Jarosz , G. Livan , M. A. Nowak , A. Swiech

The Special Theory of Relativity and Quantum Mechanics merge in the key principle of Quantum Field Theory, the Principle of Locality. We review some examples of its ``unreasonable effectiveness'' (which shows up best in the formulation of…

Mathematical Physics · Physics 2014-11-20 Sergio Doplicher