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Related papers: Markovian Solutions to Discontinuous ODEs

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Consider a one-sided Markov additive process with an upper and a lower barrier, where each can be either reflecting or terminating. For both defective and non-defective processes and all possible scenarios we identify the corresponding…

Probability · Mathematics 2013-09-20 Jevgenijs Ivanovs

In this paper we study mutual absolute continuity and singularity of probability measures on the path space which are induced by an isotropic stable L\'evy process and the purely discontinuous Girsanov transform of this process. We also…

Probability · Mathematics 2015-02-11 René L. Schilling , Zoran Vondraček

For the continuous-time and the discrete-time three-state hidden Markov model, the flux of the likelihood function up to 3-dimension of the observed process is shown explicitly. As an application, the sufficient and necessary condition of…

Probability · Mathematics 2011-01-31 Yong Chen

We provide the first polynomial-time convergence guarantees for the probability flow ODE implementation (together with a corrector step) of score-based generative modeling. Our analysis is carried out in the wake of recent results obtaining…

Machine Learning · Computer Science 2023-05-22 Sitan Chen , Sinho Chewi , Holden Lee , Yuanzhi Li , Jianfeng Lu , Adil Salim

The set of common numerical and analytical problems is introduced in the form of the generalized multidimensional discrete Poisson equation. It is shown that its solutions with square-summable discrete derivatives are unique up to a…

Mathematical Physics · Physics 2011-09-27 Roman Werpachowski

In this paper, we study one dimensional Markov processes with spatial delay. Since the seminal work of Feller, we know that virtually any one dimensional, strong, homogeneous, continuous Markov process can be uniquely characterized via its…

Probability · Mathematics 2016-10-07 Michael Salins , Konstantinos Spiliopoulos

We consider sequences $(X_t^N)_{t\geq0}$ of Markov processes in two dimensions whose fluid limit is a stable solution of an ordinary differential equation of the form $\dot{x}_t=b(x_t)$, where $b(x)={\pmatrix{-\mu 0 0 \lambda}}x+\tau(x)$…

Probability · Mathematics 2011-11-10 Amanda G. Turner

The present paper aims to investigate the metric mean dimension theory of continuous flows. We introduce the notion of metric mean dimension for continuous flows to characterize the complexity of flows with infinite topological entropy. For…

Dynamical Systems · Mathematics 2023-11-14 Rui Yang , Ercai Chen , Xiaoyao Zhou

The usual random walk on a group (homogeneous both in time and in space) is determined by a probability measure on the group. In a random walk with random transition probabilities this single measure is replaced with a stationary sequence…

Probability · Mathematics 2007-05-23 Vadim A. Kaimanovich , Yuri Kifer , Ben-Zion Rubshtein

The deterministic analog of the Markov property of a time-homogeneous Markov process is the semigroup property of solutions of an autonomous differential equation. The semigroup property arises naturally when the solutions of a differential…

Dynamical Systems · Mathematics 2019-12-03 Jorge E. Cardona , Lev Kapitanski

A dynamical systems approach to turbulence envisions the flow as a trajectory through a high-dimensional state space transiently visiting the neighbourhoods of unstable simple invariant solutions (E. Hopf, Commun. Appl. Maths 1, 303, 1948).…

Fluid Dynamics · Physics 2023-11-15 Jacob Page , Peter Norgaard , Michael P. Brenner , Rich R. Kerswell

In this paper, by introducing a new type asymptotic coupling by reflection, we explore the long time behavior of random probability measure flows associated with a large class of one-dimensional McKean-Vlasov SDEs with common noise.…

Probability · Mathematics 2024-01-17 Bao Jianhai , Wang Jian

In this paper, we employ Markov process theory to prove asymptotic results for a class of stochastic processes which arise as solutions of a stochastic evolution inclusion and are given by the representation formula \begin{align*}…

Probability · Mathematics 2018-01-23 Alexander Nerlich

We consider random walks on dynamical networks where edges appear and disappear during finite time intervals. The process is grounded on three independent stochastic processes determining the walker's waiting-time, the up-time and down-time…

Physics and Society · Physics 2018-11-28 Julien Petit , Martin Gueuning , Timoteo Carletti , Ben Lauwens , Renaud Lambiotte

Markov automata combine non-determinism, probabilistic branching, and exponentially distributed delays. This compositional variant of continuous-time Markov decision processes is used in reliability engineering, performance evaluation and…

Logic in Computer Science · Computer Science 2017-05-11 Tim Quatmann , Sebastian Junges , Joost-Pieter Katoen

Order-preserving couplings are elegant tools for obtaining robust estimates of the time-dependent and stationary distributions of Markov processes that are too complex to be analyzed exactly. The starting point of this paper is to study…

Probability · Mathematics 2009-06-02 Lasse Leskelä

This paper develops a comprehensive Markov-based framework for modelling reservoir behaviour and assessing key performance measures such as reliability and resilience. We first formulate a stochastic model for a finite-capacity dam,…

Methodology · Statistics 2026-03-05 M. L. Gámiz , N. Limnios , D. Montoro-Cazorla , M. C. Segovia-García

Given an Axiom A attractor for a $C^{1+\alpha}$ flow ($\alpha>0$), we construct a countable Markov extension with exponential return times in such a way that the inducing set is a smoothly embedded unstable disk. This avoids technical…

Dynamical Systems · Mathematics 2025-06-17 Ian Melbourne , Paulo Varandas

We present a fairly new and comprehensive approach to the study of stationary flows of the Korteweg-de Vries hierarchy. They are obtained by means of a double restriction process from a dynamical system in an infinite number of variables.…

Exactly Solvable and Integrable Systems · Physics 2009-09-25 Gregorio Falqui , Franco Magri , Marco Pedroni , Jorge P. Zubelli

We introduce a novel unit-time ordinary differential equation (ODE) flow called the preconditioned F\"{o}llmer flow, which efficiently transforms a Gaussian measure into a desired target measure at time 1. To discretize the flow, we apply…

Methodology · Statistics 2023-11-08 Zhao Ding , Yuling Jiao , Xiliang Lu , Zhijian Yang , Cheng Yuan