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We consider the behavior of extremal particles in $K$-symmetric exclusion on $\mathbb{Z}$ when the process starts from certain infinite-particle step configurations where there are no particles to the right of a maximal one. In such a…

Probability · Mathematics 2025-06-17 Michael Conroy , Adrián González Casanova , Sunder Sethuraman

This paper studies the diffusion limit for a network of infinite-server queues operating under Markov modulation (meaning that the system's parameters depend on an autonomously evolving background process). In previous papers on (primarily…

Probability · Mathematics 2017-12-13 H. M. Jansen , M. Mandjes , K. De Turck , S. Wittevrongel

We consider random instances of non-convex perceptron problems in the high-dimensional limit of a large number of examples $M$ and weights $N$, with finite load $\alpha = M/N$. We develop a formalism based on replica theory to predict the…

Disordered Systems and Neural Networks · Physics 2026-02-11 Elizaveta Demyanenko , Davide Straziota , Carlo Baldassi , Carlo Lucibello

Continuous time random walks are non-Markovian stochastic processes, which are only partly characterized by single-time probability distributions. We derive a closed evolution equation for joint two-point probability density functions of a…

Statistical Mechanics · Physics 2009-11-13 A. Baule , R. Friedrich

We study a prominent two-parametric family of diffusion processes $X_{z,z'}$ on an infinite-dimensional Thoma simplex. The family was constructed by Borodin and Olshanski in 2007 and it closely resembles Ethier-Kurtz's…

Probability · Mathematics 2024-08-08 Sergei Korotkikh

We study the zero-range process on the complete graph. It is a Markov chain model for a microcanonical ensemble. We prove that the process converges to a fluid limit. The fluid limit rapidly relaxes to the appropriate Gibbs distribution.

Probability · Mathematics 2009-06-12 Benjamin T. Graham

The goal of this expository article is a fairly self-contained account of some averaging processes of functions along sequences of the form $(\alpha^n x)^{}_{n\in\mathbb{N}}$, where $\alpha$ is a fixed real number with $| \alpha | > 1$ and…

Number Theory · Mathematics 2018-01-24 Michael Baake , Alan Haynes , Daniel Lenz

We consider a generalised diffusion equation in two dimensions for modeling diffusion on a comb-like structures. We analyse the probability distribution functions and we derive the mean squared displacement in $x$ and $y$ directions.…

Statistical Mechanics · Physics 2016-06-23 Trifce Sandev , Alexander Iomin , Holger Kantz , Ralf Metzler , Aleksei Chechkin

We introduce the {\it diffusion $K$-means} clustering method on Riemannian submanifolds, which maximizes the within-cluster connectedness based on the diffusion distance. The diffusion $K$-means constructs a random walk on the similarity…

Statistics Theory · Mathematics 2020-03-17 Xiaohui Chen , Yun Yang

Petrov constructed a diffusion process in the Kingman simplex whose unique stationary distribution is the two-parameter Poisson-Dirichlet distribution of Pitman and Yor. We show that the subset of the simplex comprising vectors whose…

Probability · Mathematics 2015-02-27 S. N. Ethier

We consider the totally asymmetric simple exclusion processes on quenched random energy landscapes. We show that the current and the diffusion coefficient differ from those for homogeneous environments. Using the mean-field approximation,…

Statistical Mechanics · Physics 2023-05-29 Issei Sakai , Takuma Akimoto

Denoising diffusion probabilistic models and score-matching models have proven to be very powerful for generative tasks. While these approaches have also been applied to the generation of discrete graphs, they have, so far, relied on…

Machine Learning · Computer Science 2023-08-17 Kilian Konstantin Haefeli , Karolis Martinkus , Nathanaël Perraudin , Roger Wattenhofer

We introduce Generator Matching, a modality-agnostic framework for generative modeling using arbitrary Markov processes. Generators characterize the infinitesimal evolution of a Markov process, which we leverage for generative modeling in a…

Machine Learning · Computer Science 2025-02-28 Peter Holderrieth , Marton Havasi , Jason Yim , Neta Shaul , Itai Gat , Tommi Jaakkola , Brian Karrer , Ricky T. Q. Chen , Yaron Lipman

We propose in this paper an analytically new construct of a diffusion model whose drift and diffusion parameters yield an exponentially time-decaying Signal to Noise Ratio in the forward process. In reverse, the construct cleverly carries…

Image and Video Processing · Electrical Eng. & Systems 2024-08-16 Tanmay Asthana , Yufang Bao , Hamid Krim

Point processes model the distribution of random point sets in mathematical spaces, such as spatial and temporal domains, with applications in fields like seismology, neuroscience, and economics. Existing statistical and machine learning…

Machine Learning · Computer Science 2024-10-31 David Lüdke , Enric Rabasseda Raventós , Marcel Kollovieh , Stephan Günnemann

The long time behavior of an absorbed Markov process is well described by the limiting distribution of the process conditioned to not be killed when it is observed. Our aim is to give an approximation's method of this limit, when the…

Probability · Mathematics 2009-05-25 Denis Villemonais

We consider graph diffusion processes constructed from finite i.i.d. samples drawn from an unknown manifold embedded in ambient Euclidean space, where the graph affinity is defined by an ambient Gaussian kernel matrix. We show that the…

Machine Learning · Statistics 2026-05-26 Xiuyuan Cheng , Nan Wu

In this paper we establish a diffusion limit for a multivariate continuous time Markov chain whose components are indexed by vertices of a finite graph. The components take values in a common finite set of non-negative integers and evolve…

Probability · Mathematics 2025-09-15 Anatolii Puhalskii , Vadim Shcherbakov

We investigate some asymptotic properties of general Markov processes conditioned not to be absorbed by moving boundaries. We first give general criteria involving an exponential convergence towards the Q-process, that is the law of the…

Probability · Mathematics 2020-05-13 William Oçafrain

In this article we study a homogeneous transient diffusion process $X$. We combine the theories of differential equations and of stochastic processes to obtain new results for homogeneous diffusion processes, generalizing the results of…

Probability · Mathematics 2013-06-07 Mykola Perestyuk , Yuliya Mishura , Georgiy Shevchenko
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