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We investigate joint temporal and contemporaneous aggregation of N independent copies of strictly stationary INteger-valued AutoRegressive processes of order 1 (INAR(1)) with random coefficient $\alpha\in(0,1)$ and with idiosyncratic…

Probability · Mathematics 2021-10-19 Matyas Barczy , Fanni K. Nedényi , Gyula Pap

Complex systems of many interacting components exhibit patterns of recurrence and emergent behaviors in their time evolution that can be understood from a new perspective of physics of information dynamics, modeled after one such system,…

Disordered Systems and Neural Networks · Physics 2026-01-27 Uday S. Goteti , Shane A. Cybart , Robert C. Dynes

Consider a system of interacting particles indexed by the nodes of a graph whose vertices are equipped with marks representing parameters of the model such as the environment or initial data. Each particle takes values in a countable state…

Probability · Mathematics 2022-10-18 Ankan Ganguly , Kavita Ramanan

We propose a scalable framework for inference in an inhomogeneous Poisson process modeled by a continuous sigmoidal Cox process that assumes the corresponding intensity function is given by a Gaussian process (GP) prior transformed with a…

Machine Learning · Statistics 2019-06-10 Virginia Aglietti , Edwin V. Bonilla , Theodoros Damoulas , Sally Cripps

We consider exploration algorithms of the random sequential adsorption type both for homogeneous random graphs and random geometric graphs based on spatial Poisson processes. At each step, a vertex of the graph becomes active and its…

Probability · Mathematics 2017-11-22 Paola Bermolen , Matthieu Jonckheere , Jaron Sanders

We construct a model of strategic imitation in an arbitrary network of players who interact through an additive game. Assuming a discrete time update, we show a condition under which the resulting difference equations converge to consensus.…

Dynamical Systems · Mathematics 2019-04-15 Christopher Griffin , Sarah Rajtmajer , Anna Squicciarini , Andrew Belmonte

In this paper we derive and analyse mean-field models for the dynamics of groups of individuals undergoing a random walk. The random motion of individuals is only influenced by the perceived densities of the different groups present as well…

We propose a mean-field model of interacting point processes where each process has a memory of the time elapsed since its last event (age) and its recent past (leaky memory), generalizing Age-dependent Hawkes processes. The model is…

Probability · Mathematics 2021-12-07 Valentin Schmutz

We considered diffusion-driven processes on small-world networks with distance-dependent random links. The study of diffusion on such networks is motivated by transport on randomly folded polymer chains, synchronization problems in…

Statistical Mechanics · Physics 2007-09-05 Balazs Kozma , Matthew B. Hastings , G. Korniss

Motivated by an application in wireless telecommunication networks, we consider a two-type continuum-percolation problem involving a homogeneous Poisson point process of users and a stationary and ergodic point process of base stations.…

Probability · Mathematics 2015-02-19 Christian Hirsch

We provide a Poisson approximation result for dependent thinnings of Gibbs point processes as well as qualitative and quantitative central limit theorems for geometric functionals of Gibbs point processes in increasing observation windows.…

Probability · Mathematics 2026-01-27 Christian Hirsch , Moritz Otto , Anne Marie Svane

Marked point process data arise when events occur in a space with event-level marks. We study clustering of replicated marked Poisson point processes and introduce Dirichlet process mixtures of marked Poisson point processes, a Bayesian…

Methodology · Statistics 2026-05-12 Minsung Choi , Seonghyun Jeong

Networks play a central role in modern data analysis, enabling us to reason about systems by studying the relationships between their parts. Most often in network analysis, the edges are given. However, in many systems it is difficult or…

Machine Learning · Statistics 2014-02-06 Scott W. Linderman , Ryan P. Adams

A complex contagion is an infectious process in which individuals may require multiple transmissions before changing state. These are used to model behaviors if an individual only adopts a particular behavior after perceiving a consensus…

Physics and Society · Physics 2015-06-29 Joel C. Miller

A recent dynamic mean-field theory for sequence processing in fully connected neural networks of Hopfield-type (During, Coolen and Sherrington, 1998) is extended and analized here for a symmetrically diluted network with finite connectivity…

Disordered Systems and Neural Networks · Physics 2009-11-10 W. K. Theumann

In the present work we demonstrate the use of a parcellation free connectivity model based on Poisson point processes. This model produces for each subject a continuous bivariate intensity function that represents for every possible pair of…

Neurons and Cognition · Quantitative Biology 2016-11-21 Daniel Moyer , Boris A. Gutman , Joshua Faskowitz , Neda Jahanshad , Paul M. Thompson

Aldous, Evans and Pitman (1998) studied the behavior of the fragmentation process derived from deleting the edges of a uniform random tree on $n$ labelled vertices. In particular, they showed that, after proper rescaling, the above…

Probability · Mathematics 2025-09-03 Gabriel Berzunza Ojeda , Cecilia Holmgren

Recently the so-called Prabhakar generalization of the fractional Poisson counting process attracted much interest for his flexibility to adapt real world situations. In this renewal process the waiting times between events are IID…

Probability · Mathematics 2020-12-10 Thomas M. Michelitsch , Federico Polito , Alejandro P. Riascos

The dynamical emergence (and subsequent intermittent breakdown) of collective behavior in complex systems is described as a non-Poisson renewal process, characterized by a waiting-time distribution density $\psi (\tau)$ for the time…

Statistical Mechanics · Physics 2007-05-23 Paolo Allegrini , Mauro Bologna , Paolo Grigolini , Bruce J. West

Idealized networks of integrate-and-fire neurons with impulse-like interactions obey McKean-Vlasov diffusion equations in the mean-field limit. These equations are prone to blowups: for a strong enough interaction coupling, the mean-field…

Probability · Mathematics 2022-05-17 Thibaud Taillefumier , Phillip Whitman
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