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We present Lyapunov-type conditions for non-strong ergodicity of Markov processes. Some concrete models are discussed including diffusion processes on Riemannian manifolds and Ornstein-Uhlenbeck processes driven by symmetric $\alpha$-stable…

Probability · Mathematics 2020-04-20 Yong-Hua Mao , Tao Wang

We consider deep multivariate models for heterogeneous collections of random variables. In the context of computer vision, such collections may e.g. consist of images, segmentations, image attributes, and latent variables. When developing…

Machine Learning · Computer Science 2026-02-03 Dmitrij Schlesinger , Boris Flach , Alexander Shekhovtsov

This paper proposes a notion of branching bisimilarity for non-deterministic probabilistic processes. In order to characterize the corresponding notion of rooted branching probabilistic bisimilarity, an equational theory is proposed for a…

Logic in Computer Science · Computer Science 2025-02-11 Rob van Glabbeek , Jan Friso Groote , Erik de Vink

The phenomenological dissipation of the Bloch equations is reexamined in the context of completely positive maps. Such maps occur if the dissipation arises from a reduction of a unitary evolution of a system coupled to a reservoir. In such…

Quantum Physics · Physics 2015-06-26 Sonja Daffer , Krzysztof Wodkiewicz , John K. McIver

Stochastic branching processes are a classical model for describing random trees, which have applications in numerous fields including biology, physics, and natural language processing. In particular, they have recently been proposed to…

Logic in Computer Science · Computer Science 2012-06-07 Taolue Chen , Klaus Dräger , Stefan Kiefer

There are some positively divisible non-Markovian processes whose transition matrices satisfy the Chapman-Kolmogorov equation. These processes should also satisfy the Kolmogorov consistency conditions, an essential requirement for a process…

Probability · Mathematics 2024-01-24 Bilal Canturk , Heinz-Peter Breuer

We introduce Multi-Environment Markov Decision Processes (MEMDPs) which are MDPs with a set of probabilistic transition functions. The goal in a MEMDP is to synthesize a single controller with guaranteed performances against all…

Logic in Computer Science · Computer Science 2014-12-04 Jean-François Raskin , Ocan Sankur

This paper studies Markov Decision Processes under parameter uncertainty. We adapt the distributionally robust optimization framework, and assume that the uncertain parameters are random variables following an unknown distribution, and…

Systems and Control · Computer Science 2015-05-14 Pengqian Yu , Huan Xu

This paper continues the research project launched in [Constr. Approx. (2025) https://doi.org/10.1007/s00365-023-09675-9] and aimed at studying time-inhomogeneous one-dimensional branching processes (mainly on a continuous but also on a…

Probability · Mathematics 2025-12-16 Pavel Gumenyuk , Takahiro Hasebe , José-Luis Pérez

We consider a stochastic process in which independent identically distributed random matrices are multiplied and where the Lyapunov exponent of the product is positive. We continue multiplying the random matrices as long as the norm,…

Statistical Mechanics · Physics 2018-03-14 Michael Wilkinson , John Grant

The problems on the location of the matrix spectrum inside or outside domains bounded by ellipses or parabolas are studied. Special Lyapunov-type equations are connected with these problems. Theorems about the unique solvability of such…

Classical Analysis and ODEs · Mathematics 2023-12-20 G. V. Demidenko , Z. Wang

The subcritical Markov branching process X(t) starting with one particle as the initial condition has the ultimate extinction probability q = 1. The branching mechanism in consideration is defined by the mixture of logarithmic distributions…

Probability · Mathematics 2023-12-06 Penka Mayster , Assen Tchorbadjieff

A continuous-time particle system on the real line satisfying the branching property and an exponential integrability condition is called a branching L\'evy process, and its law is characterized by a triplet $(\sigma^2,a,\Lambda)$. We…

Probability · Mathematics 2022-02-25 Bastien Mallein , Quan Shi

We construct a modified continuous-state branching process whose Malthusian parameter is replaced by another when passing below a certain level. The construction is obtained via a Lamperti-like transform applied to a refracted L\'evy…

Probability · Mathematics 2016-12-01 Antonio Murillo-Salas , José Luis Pérez , Arno Siri-Jégousse

The goal of this article is to contribute towards the conceptual and quantitative understanding of the evolutionary benefits for (microbial) populations to maintain a seed bank (consisting of dormant individuals) when facing fluctuating…

Probability · Mathematics 2024-07-02 Jochen Blath , Felix Hermann , Martin Slowik

Let (Z n) n$\ge$0 with Z n = (Z n (i, j)) 1$\le$i,j$\le$p be a p multi-type critical branching process in random environment, and let M n be the expectation of Z n given a fixed environment. We prove theorems on convergence in distribution…

Probability · Mathematics 2021-10-27 E. Le Page , M. Peigné , C. Pham

We study time continuous branching processes with exponentially distributed lifetimes, with two types of cells that proliferate according to binary fission. A range of possible system dynamics are considered, each of which is characterized…

Probability · Mathematics 2022-04-27 Nam H Nguyen , Marek Kimmel

We consider a type of random processes which satisfies the conditional increment condition and obtain an estimate for the tail probability and a Doob-type inequality of the maximum of the process. The main result is that, for processes…

Probability · Mathematics 2016-06-21 Xuan Liu

Potential theory is a central tool to understand and analyse Markov processes. In this article, we develop its probabilistic counterpart for branching Markov chains. Specifically, we examine versions of quasi-processes or interlacements…

Probability · Mathematics 2023-11-07 Steffen Dereich , Martin Maiwald

Simple Hartree-type equations lead to dynamics of a subsystem that is not completely positive in the sense accepted in mathematical literature. In the linear case this would imply that negative probabilities have to appear for some system…

Quantum Physics · Physics 2009-10-30 Marek Czachor , Maciej Kuna
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