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Models of random phylogenetic networks have been used since the inception of the field, but the introduction and rigorous study of mathematically tractable models is a much more recent topic that has gained momentum in the last 5 years.…

Populations and Evolution · Quantitative Biology 2024-11-20 François Bienvenu

This paper is a greatly expanded version of a talk I gave in April 2009 at KunenFest. It describes Ken's work in algebra, particularly using automated deduction tools.

History and Overview · Mathematics 2012-10-01 Michael Kinyon

Stochastic network calculus is a newly developed theory for stochastic service guarantee analysis of computer networks. In the current stochastic network calculus literature, its fundamental models are based on the cumulative amount of…

Performance · Computer Science 2011-12-14 Jing Xie , Yuming Jiang , Min Xie

This paper reviews existing work in software engineering that applies statistical causal inference methods. These methods aim at estimating causal effects from observational data. The review covers 32 papers published between 2010 and 2022.…

Software Engineering · Computer Science 2023-03-24 Julien Siebert

This popular article provides a short summary of the progress and prospects in Weather and Climate Modelling for the benefit of high school and undergraduate college students and early career researchers. Although this is not a…

Atmospheric and Oceanic Physics · Physics 2020-11-24 R Krishnan , Manmeet Singh , Ramesh Vellore , Milind Mujumdar

The Skorokhod reflection of a continuous semimartingale is unfolded, in a possibly skewed manner, into another continuous semimartingale on an enlarged probability space according to the excursion-theoretic methodology of Prokaj (2009).…

Probability · Mathematics 2014-07-18 Tomoyuki Ichiba , Ioannis Karatzas

This article is based on lecture notes for the Marie Curie Training school "Initial Training on Numerical Methods for Active Matter". It provides an introductory overview of modeling approaches for active matter and is primarily targeted at…

Soft Condensed Matter · Physics 2021-02-26 L. Hecht , J. C. Ureña , B. Liebchen

The state of art in spin glass field theory is reviewed.

Statistical Mechanics · Physics 2008-02-03 C. De Dominicis , I. Kondor , T. Temesvari

Machine learning encompasses a broad range of algorithms and modeling tools used for a vast array of data processing tasks, which has entered most scientific disciplines in recent years. We review in a selective way the recent research on…

This manuscript treats the diverse applications of bricks within modern representation theory and several related domains, and reviews the recent developments and new results on bricks (a.k.a Schur representations). The current survey is an…

Representation Theory · Mathematics 2025-08-19 Kaveh Mousavand , Charles Paquette

An introduction and overview is given of the theory of spin glasses and its application.

Disordered Systems and Neural Networks · Physics 2007-05-23 David Sherrington

The paper is based on lectures on the internal structure and evolution of the Sun. It contains an outline of observational and theoretical elements of the Standard Solar Model, emphasizing also recent research results on solar rotation,…

Astrophysics · Physics 2011-03-01 H. J. Haubold , A. M. Mathai

Rejoinder: Classifier Technology and the Illusion of Progress [math.ST/0606441]

Statistics Theory · Mathematics 2007-06-13 David J. Hand

This is a note on logistic regression models and logistic kernel machine models. It contains derivations to some of the expressions in a paper -- SNP Set Analysis for Detecting Disease Association Using Exon Sequence Data -- submitted to…

Applications · Statistics 2011-03-07 Ru Wang , Jie Peng , Pei Wang

This review presents various aspects of a mean-field spin glass model known as the p-spin spherical spin glass model, which has raised a lot of interest in the study of spin glasses, and also for its possible links with a mean-field theory…

Disordered Systems and Neural Networks · Physics 2008-02-03 A. Barrat

This paper reviews recent developments in statistical structure learning; namely, Bayesian model reduction. Bayesian model reduction is a method for rapidly computing the evidence and parameters of probabilistic models that differ only in…

Methodology · Statistics 2019-10-15 Karl Friston , Thomas Parr , Peter Zeidman

Synthetic control (SC) methods are commonly used to estimate the treatment effect on a single treated unit in panel data settings. An SC is a weighted average of control units built to match the treated unit, with weights typically…

Methodology · Statistics 2023-02-21 Xu Shi , Kendrick Li , Wang Miao , Mengtong Hu , Eric Tchetgen Tchetgen

The article analyzes the historical aspect of the formation of computer modeling as one of the perspective directions of educational process development. The notion of "system of computer modeling", conceptual model of system of computer…

Other Computer Science · Computer Science 2020-05-18 Svitlana H. Lytvynova

This is an introductory article to the theory of multiple gaps.

Logic · Mathematics 2014-06-26 Antonio Avilés

In medical image analysis, the cost of acquiring high-quality data and their annotation by experts is a barrier in many medical applications. Most of the techniques used are based on supervised learning framework and need a large amount of…

Computer Vision and Pattern Recognition · Computer Science 2022-10-20 Siladittya Manna , Saumik Bhattacharya , Umapada Pal
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