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A study of time homogeneous, real valued Markov processes with a special property and a non-atomic initial distribution is provided. The new notion of a function of evolution of distribution which determines the dependency between one…

Probability · Mathematics 2022-07-04 Tomasz Bielecki , Jacek Jakubowski , Maciej Wiśniewolski

We establish sufficient conditions for exponential convergence to a unique quasi-stationary distribution in the total variation norm. These conditions also ensure the existence and exponential ergodicity of the Q-process, the process…

Probability · Mathematics 2023-08-01 Aurélien Velleret

Some topological properties of stochastic flow $\varphi_t(x)$ generated by stochastic differential equation in a ${\mathbb R}^d_+$ with normal reflection at the boundary are investigated. Sobolev differentiability in initial condition is…

Probability · Mathematics 2008-10-28 Andrey Pilipenko

To overcome topological constraints and improve the expressiveness of normalizing flow architectures, Wu, K\"ohler and No\'e introduced stochastic normalizing flows which combine deterministic, learnable flow transformations with stochastic…

Machine Learning · Computer Science 2022-12-02 Paul Hagemann , Johannes Hertrich , Gabriele Steidl

In this article I will prove new representation for the Levi-Civita connection in terms of the stochastic flow corresponding to Brownian motion on manifold.

Probability · Mathematics 2008-02-25 M. Neklyudov

The influence of a time-periodic forcing on stochastic processes can essentially be emphasized in the large time behaviour of their paths. The statistics of transition in a simple Markov chain model permits to quantify this influence. In…

Probability · Mathematics 2013-03-27 Samuel Herrmann , Damien Landon

In the paper we consider a stochastic model which called Markov Q-processes that forms a continuous-time Markov population system. Markov Q-processes are defined as stochastic Markov branching processes with trajectories continuing in the…

Statistics Theory · Mathematics 2022-04-01 Azam Imomov , Zukhriddin Nazarov

We consider a pair of correlated processes {Z_n} and {S_n} (two sided), where the former is observable and the later is hidden. The uncertainty in the estimation of Z_n upon its finite past history is H(Z_n|Z_0^{n-1}), and for estimation of…

Information Theory · Computer Science 2007-07-13 Mohammad Rezaeian

These notes survey some aspects of discrete-time chaotic calculus and its applications, based on the chaos representation property for i.i.d. sequences of random variables. The topics covered include the Clark formula and predictable…

Probability · Mathematics 2018-06-04 Nicolas Privault

For a series of Markov processes we prove stochastic duality relations with duality functions given by orthogonal polynomials. This means that expectations with respect to the original process (which evolves the variable of the orthogonal…

Probability · Mathematics 2017-02-01 Chiara Franceschini , Cristian Giardinà

This is survey of some recent results connecting random matrices, non-colliding processes and queues.

Probability · Mathematics 2008-04-16 Neil O'Connell

We survey the published work of Harry Kesten in probability theory, with emphasis on his contributions to random walks, branching processes, percolation, and related topics. A complete bibliography is included of his publications.

Probability · Mathematics 2020-11-16 Geoffrey R. Grimmett

This paper offers a personal review of some things we've learned about rates of convergence of Markov chains to their stationary distributions. The main topic is ways of speeding up diffusive behavior. It also points to open problems and…

Statistics Theory · Mathematics 2013-10-01 Persi Diaconis

This special issue collects contributions from the participants of the "Information in Dynamical Systems and Complex Systems" workshop, which cover a wide range of important problems and new approaches that lie in the intersection of…

Chaotic Dynamics · Physics 2015-05-19 Erik M. Bollt , Jie Sun

We consider random processes that are history-dependent, in the sense that the distribution of the next step of the process at any time depends upon the entire past history of the process. In general, therefore, the Markov property cannot…

Probability · Mathematics 2019-11-19 Peter Clifford , David Stirzaker

A brief presentation of basics of the theory of Tchebycheff and Markov systems of functions and its applications to extremal problems for integrals of such functions is given. The results, as well as all the necessary definitions, are…

Optimization and Control · Mathematics 2011-07-19 Iosif Pinelis

Stochastic processes generated by non-stationary distributions are difficult to represent with conventional models such as Gaussian processes. This work presents Recurrent Autoregressive Flows as a method toward general stochastic process…

Machine Learning · Computer Science 2020-06-20 John Mern , Peter Morales , Mykel J. Kochenderfer

We use the abstract method of (local) martingale problems in order to give criteria for convergence of stochastic processes. Extending previous notions, the formulation we use is neither restricted to Markov processes (or semimartingales),…

Probability · Mathematics 2021-08-27 David Criens , Peter Pfaffelhuber , Thorsten Schmidt

We collect and present in a unified way several results in recent years about the elastic flow of curves and networks, trying to draw the state of the art of the subject. In particular, we give a complete proof of global existence and…

Analysis of PDEs · Mathematics 2023-03-30 Carlo Mantegazza , Alessandra Pluda , Marco Pozzetta

We consider a multidimensional time-homogeneous dynamical system and add a randomly perturbed time-dependent deterministic signal to some of its components, giving rise to a high-dimensional system of stochastic differential equations,…

Probability · Mathematics 2019-08-02 Simon Holbach
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