English
Related papers

Related papers: The saturated pairwise interaction Gibbs point pro…

200 papers

The symbiotic branching model describes the dynamics of a spatial two-type population, where locally particles branch at a rate given by the frequency of the other type combined with nearest-neighbour migration. This model generalizes…

Probability · Mathematics 2021-07-01 Jochen Blath , Marcel Ortgiese

Advances in cellular imaging technologies, especially those based on fluorescence in situ hybridization (FISH) now allow detailed visualization of the spatial organization of human or bacterial cells. Quantifying this spatial organization…

We develop a Gaussian process framework for learning interaction kernels in multi-species interacting particle systems from trajectory data. Such systems provide a canonical setting for multiscale modeling, where simple microscopic…

Machine Learning · Statistics 2025-11-05 Jinchao Feng , Charles Kulick , Sui Tang

We introduce a probabilistic pairwise \emph{attraction--repulsion} model for opinion dynamics on multilayer social networks, in which agents hold layer-specific states and interact through random matchings that couple multiple, time-varying…

Dynamical Systems · Mathematics 2025-12-23 Hsin-Lun Li

Network data often take the form of repeated interactions between senders and receivers tabulated over time. A primary question to ask of such data is which traits and behaviors are predictive of interaction. To answer this question, a…

Methodology · Statistics 2013-04-09 Patrick O. Perry , Patrick J. Wolfe

Several coupled maps models are sketched and reviewed in this short communication. First, a discrete logistic type model that was proposed for the symbiotic interaction of two species. Second, a model of many of these symbiotic species…

Adaptation and Self-Organizing Systems · Physics 2019-08-22 Ricardo Lopez-Ruiz

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

When analyzing animal movement, it is important to account for interactions between individuals. However, statistical models for incorporating interaction behavior in movement models are limited. We propose an approach that models dependent…

Applications · Statistics 2015-08-04 James C. Russell , Ephraim M. Hanks , Murali Haran

We study a model ecosystem by means of dynamical techniques from disordered systems theory. The model describes a set of species subject to competitive interactions through a background of resources, which they feed upon. Additionally…

Populations and Evolution · Quantitative Biology 2009-11-13 Yoshimi Yoshino , Tobias Galla , Kei Tokita

We introduce a nonlinear modification of the classical Hawkes process, which allows inhibitory couplings between units without restrictions. The resulting system of interacting point processes provides a useful mathematical model for…

Probability · Mathematics 2009-11-03 Stefano Cardanobile , Stefan Rotter

In order to model real ecological systems one has to consider many species that interact in complex ways. However, most of the recent theoretical studies have been restricted to few species systems with rather trivial interactions. The few…

Populations and Evolution · Quantitative Biology 2014-04-11 Shahir Mowlaei , Ahmed Roman , Michel Pleimling

Joint species distribution modeling is attracting increasing attention these days, acknowledging the fact that individual level modeling fails to take into account expected dependence/interaction between species. These models attempt to…

Methodology · Statistics 2019-08-27 Alan E. Gelfand , Shinichiro Shirota

The emergence and impact of tipping points have garnered significant interest in both the social and natural sciences. Despite widespread recognition of the importance of feedbacks between human and natural systems, it is often assumed that…

The intensity of a Gibbs point process is usually an intractable function of the model parameters. For repulsive pairwise interaction point processes, this intensity can be expressed as the Laplace transform of some particular function.…

Methodology · Statistics 2017-12-11 Jean-François Coeurjolly , Frédéric Lavancier

We propose a novel framework for analyzing the dynamics of distribution shift in real-world systems that captures the feedback loop between learning algorithms and the distributions on which they are deployed. Prior work largely models…

Machine Learning · Computer Science 2023-10-31 Lauren Conger , Franca Hoffmann , Eric Mazumdar , Lillian Ratliff

Because most natural phenomena exhibit dependence at multiple scales like locations of earthquakes or forest fire occurrences, spatio-temporal single-scale point process models are unrealistic in many applications. This motivates us to…

Applications · Statistics 2020-12-18 Morteza Raeisi , Florent Bonneu , Edith Gabriel

Inspired by applications in sports where the skill of players or teams competing against each other varies over time, we propose a probabilistic model of pairwise-comparison outcomes that can capture a wide range of time dynamics. We…

Machine Learning · Statistics 2019-05-20 Lucas Maystre , Victor Kristof , Matthias Grossglauser

The decentralized patch distribution mechanism holds significant promise as an alternative to its centralized counterpart. For the purpose of accurately evaluating the performance of the decentralized patch distribution mechanism and based…

Social and Information Networks · Computer Science 2023-02-27 Lu-Xing Yang , Xiaofan Yang , Qingyi Zhu , Chenquan Gan

We study a non-local two species cross-interaction model with cross-diffusion. We propose a positivity preserving finite volume scheme based on the numerical method introduced in Ref. [15] and explore this new model numerically in terms of…

Analysis of PDEs · Mathematics 2017-05-10 J. A. Carrillo , Y. Huang , M. Schmidtchen

Inference for belief networks using Gibbs sampling produces a distribution for unobserved variables that differs from the correct distribution by a (usually) unknown error, since convergence to the right distribution occurs only…

Artificial Intelligence · Computer Science 2013-01-18 Michael Harvey , Radford M. Neal