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We use mean field theory to study the response properties of a simple randomly-connected model cortical network of leaky integrate-and-fire neurons with balanced excitation and inhibition. The formulation permits arbitrary temporal…

Disordered Systems and Neural Networks · Physics 2007-05-23 John Hertz , Barry Richmond , Kristian Nilsen

We propose a novel tie-oriented model for longitudinal event network data. The generating mechanism is assumed to be a multivariate Poisson process that governs the onset and repetition of yearly observed events with two separate intensity…

Applications · Statistics 2021-09-28 Cornelius Fritz , Paul W. Thurner , Göran Kauermann

In many contexts such as queuing theory, spatial statistics, geostatistics and meteorology, data are observed at irregular spatial positions. One model of this situation involves considering the observation points as generated by a Poisson…

Statistics Theory · Mathematics 2007-08-07 Tucker McElroy , Dimitris N. Politis

Stochastic processes with multiplicative noise have been studied independently in several different contexts over the past decades. We focus on the regime, found for a generic set of control parameters, in which stochastic processes with…

Statistical Mechanics · Physics 2015-06-25 D. Sornette

It is demonstrated that World War II casualty data display statistical structure that would be expected from multifractal data. Given that the data displayed these properties, it is shown how the existence of power-law tails in the…

Data Analysis, Statistics and Probability · Physics 2012-04-03 Michael Kyle Lauren

Adversarial examples pose a unique challenge for deep learning systems. Despite recent advances in both attacks and defenses, there is still a lack of clarity and consensus in the community about the true nature and underlying properties of…

Computer Vision and Pattern Recognition · Computer Science 2021-11-02 Shishira R Maiya , Max Ehrlich , Vatsal Agarwal , Ser-Nam Lim , Tom Goldstein , Abhinav Shrivastava

Does a high dispersal rate provide a competitive advantage when risking competitive exclusion? To this day, the theoretical literature cannot answer this question in full generality. The present paper focuses on the simplest mathematical…

Analysis of PDEs · Mathematics 2020-02-24 Léo Girardin

The conflicts between armed groups often go on for years. The classical model of such conflicts accounts for the number of participants and for the technology level of the equipment of the groups. Below we extend this model in order to…

Physics and Society · Physics 2008-10-23 Nikolay K. Vitanov , Stojcho Panchev

Phase transitions, characterized by abrupt shifts between macroscopic patterns of organization, are ubiquitous in complex systems. Despite considerable research in the physical and natural sciences, the empirical study of this phenomenon in…

Physics and Society · Physics 2023-11-15 Dan Braha

Stips, Macias, Coughlan, Garcia-Gorriz, and Liang (2016, Nature Scientific Reports) use information flows (Liang, 2008, 2014) to establish causality from various forcings to global temperature. We show that the formulas being used hinges on…

Applications · Statistics 2021-03-22 Philippe Goulet Coulombe , Maximilian Göbel

Tipping points have been shown to be ubiquitous, both in models and empirically in a range of physical and biological systems. The question of how tipping points cascade through systems has been less well studied and is an important one. A…

Dynamical Systems · Mathematics 2020-11-19 Abhishek Mallela , Alan Hastings

We present certain mathematical aspects of an information method which was formulated in an attempt to investigate diffusion phenomena. We imagine a regular dynamical hamiltonian systems under the random perturbation of thermal (molecular)…

Statistical Mechanics · Physics 2007-05-23 Qiuping A. Wang , Wei Li

We introduce notions of safety, liveness, and fairness, as commonly used in temporal reasoning, to quantitative (bipolar) argumentation dialogues where repeated inferences are drawn from argumentation graphs with weighted nodes. Between…

Multiagent Systems · Computer Science 2026-05-25 Arunavo Ganguly , Julian Alfredo Mendez , Timotheus Kampik

We use standard physics techniques to model trading and price formation in a market under the assumption that order arrival and cancellations are Poisson random processes. This model makes testable predictions for the most basic properties…

Statistical Mechanics · Physics 2013-05-29 Marcus G. Daniels , J. Doyne Farmer , Laszlo Gillemot , Giulia Iori , Eric Smith

We analyze four models of epidemic spreading using a stochastic approach in which the primary stochastic variables are the numbers of individuals in each class. The stochastic approach is described by a master equation and the transition…

Statistical Mechanics · Physics 2020-10-28 Tânia Tomé , Mário J. de Oliveira

This paper deals with the stochastic modeling of a class of heterogeneous population in a random environment, called birth-death-swap. In addition to demographic events, swap events, i.e. moves between subgroups, occur in the population.…

Probability · Mathematics 2024-02-28 Sarah Kaakai , Nicole El Karoui

Understanding human dynamics is of major scientific and practical importance and can be increasingly addressed in a quantitative fashion thanks to electronic records capturing various human activity patterns. The authors of Ref. [1] revisit…

Data Analysis, Statistics and Probability · Physics 2007-05-23 A. -L. Barabasi , K. -I. Goh , A. Vazquez

Population dynamics of a competitive two-species system under the influence of random events are analyzed and expressions for the steady-state population mean, fluctuations, and cross-correlation of the two species are presented. It is…

Populations and Evolution · Quantitative Biology 2020-02-19 M. M. Tehrani , S. Soltanieh

The full family of discrete logistic maps has been widely studied both as a canonical example of the period-doubling route to chaos, and as a model of natural processes. In this paper we present a study of the stochastic process described…

Dynamical Systems · Mathematics 2025-09-09 Kimberly Ayers , Ami Radunskaya

We study statistical inference and distributionally robust solution methods for stochastic optimization problems, focusing on confidence intervals for optimal values and solutions that achieve exact coverage asymptotically. We develop a…

Machine Learning · Statistics 2018-07-03 John Duchi , Peter Glynn , Hongseok Namkoong
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