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Multivariate Hawkes process provides a powerful framework for modeling temporal dependencies and event-driven interactions in complex systems. While existing methods primarily focus on uncovering causal structures among observed…

Machine Learning · Computer Science 2026-03-03 Songyao Jin , Biwei Huang

Event Causality Identification (ECI) has become an essential task in Natural Language Processing (NLP), focused on automatically detecting causal relationships between events within texts. This comprehensive survey systematically…

Computation and Language · Computer Science 2025-07-25 Qing Cheng , Zefan Zeng , Xingchen Hu , Yuehang Si , Zhong Liu

A significant portion of roads, particularly in densely populated developing countries, lacks explicitly defined right-of-way rules. These understructured roads pose substantial challenges for autonomous vehicle motion planning, where…

Current causal discovery approaches require restrictive model assumptions in the absence of interventional data to ensure structure identifiability. These assumptions often do not hold in real-world applications leading to a loss of…

Machine Learning · Statistics 2025-06-25 Anish Dhir , Ruby Sedgwick , Avinash Kori , Ben Glocker , Mark van der Wilk

This paper concerns the modeling and numerical simulation of the process of speciation. In particular, given conditions for which one or more speciation events within an ecosystem occur, our aim is to develop the necessary modeling and…

Populations and Evolution · Quantitative Biology 2021-10-08 Mats K. Brun , Elyes Ahmed , Jan Martin Nordbotten , Nils Christian Stenseth

In many indigenous societies, people are categorised into several cultural groups, or clans, within which they believe to share ancestors. Clan attributions provide certain rules for marriage and descent. Such rules between clans constitute…

Physics and Society · Physics 2021-12-07 Kenji Itao , Kunihiko kaneko

Event Structures (ESs) are mainly concerned with the representation of causal relationships between events, usually accompanied by other event relations capturing conflicts and disabling. Among the most prominent variants of ESs are Prime…

Logic in Computer Science · Computer Science 2013-07-30 Youssef Arbach , Kirstin Peters , Uwe Nestmann

This paper introduces a practical sampling method for training surrogate models in the context of uncertainty propagation. We propose a heuristic method to uniformly draw samples within highest density regions of the density given by the…

Methodology · Statistics 2025-09-15 Jocelyn Minini , Micha Wasem

In this document and the accompanying documents we describe a data model (Simulation Data Model) describing numerical computer simulations of astrophysical systems. The primary goal of this standard is to support discovery of simulations by…

Instrumentation and Methods for Astrophysics · Physics 2019-05-22 Gerard Lemson , Laurent Bourges , Miguel Cervino , Claudio Gheller , Norman Gray , Franck LePetit , Mireille Louys , Benjamin Ooghe , Rick Wagner , Herve Wozniak

This article considers state estimation and veri cation problems for an important class of man-made cyber-physical systems called Discrete-Event Systems (DES).

Systems and Control · Computer Science 2019-03-28 Xiang Yin

We explore the relationship among model fidelity, experimental design, and parameter estimation in sloppy models. We show that the approximate nature of mathematical models poses challenges for experimental design in sloppy models. In many…

Quantitative Methods · Quantitative Biology 2017-02-08 Andrew White , Malachi Tolman , Howard D. Thames , Hubert Rodney Withers , Kathy A. Mason , Mark K. Transtrum

We develop a way of simulating disease spread in networks faster at the cost of some accuracy. Instead of a discrete event simulation (DES) we use a discrete time simulation. This aggregates events into time periods. We prove a bound on the…

Dynamical Systems · Mathematics 2013-04-30 Aaron Lucas , Benjamin Armbruster

This paper thoroughly investigates a range of popular DE configurations to identify components responsible for the emergence of structural bias - recently identified tendency of the algorithm to prefer some regions of the search space for…

Neural and Evolutionary Computing · Computer Science 2021-05-25 Fabio Caraffini , Anna V. Kononova , David Corne

The failure diagnosis for {\it discrete event systems} (DESs) has been given considerable attention in recent years. Both on-line and off-line diagnostics in the framework of DESs was first considered by Lin Feng in 1994, and particularly…

Artificial Intelligence · Computer Science 2007-05-23 Zhujun Fan

Models defined by stochastic differential equations (SDEs) allow for the representation of random variability in dynamical systems. The relevance of this class of models is growing in many applied research areas and is already a standard…

Methodology · Statistics 2014-08-06 Umberto Picchini

Event-based models (EBM) are a class of disease progression models that can be used to estimate temporal ordering of neuropathological changes from cross-sectional data. Current EBMs only handle scalar biomarkers, such as regional volumes,…

Machine Learning · Computer Science 2019-03-11 Vikram Venkatraghavan , Florian Dubost , Esther E. Bron , Wiro J. Niessen , Marleen de Bruijne , Stefan Klein

Sepsis is a life-threatening and serious global health issue. This study combines knowledge with available hospital data to investigate the potential causes of Sepsis that can be affected by policy decisions. We investigate the underlying…

Machine Learning · Computer Science 2025-02-19 Bruno Petrungaro , Neville K. Kitson , Anthony C. Constantinou

Deterministic continuum models formulated in terms of non-local partial differential equations for the evolutionary dynamics of populations structured by phenotypic traits have been used recently to address open questions concerning the…

Populations and Evolution · Quantitative Biology 2020-10-14 Aleksandra Ardaševa , Robert A. Gatenby , Alexander R. A. Anderson , Helen M. Byrne , Philip K. Maini , Tommaso Lorenzi

Event-driven molecular dynamics is a valuable tool in condensed and soft matter physics when particles can be modeled as hard objects or more generally if their interaction potential can be modeled in a stepwise fashion. Hard spheres model…

Computational Physics · Physics 2015-05-19 Cristiano De Michele

Calibration is a vital step in the development of rigorous digital models of diverse physical and chemical processes, yet one which is highly time- and labour-intensive. In this paper, we introduce a novel tool, Autonomous Calibration and…