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Related papers: Introduction to the SK model

200 papers

Basic principles of mathematical modeling are reviewed in this book, with the focus on physics and its practical applications, and examples of selected mathematical methods are presented. Most of the models have been imported from physics…

Classical Physics · Physics 2025-07-14 Sergej Pankratow

We prove a simple identity relating the $k$th moment of the partition function $Z_N(\cdot)$ in the SK model to the $N$th moment of the partition function $Z_k(\cdot)$. As a corollary we find a characterisation of the limit $\lim_{N \to…

Probability · Mathematics 2015-09-17 Sergey Bocharov

This paper reviews developments in statistics for spatial point processes obtained within roughly the last decade. These developments include new classes of spatial point process models such as determinantal point processes, models…

Methodology · Statistics 2016-09-06 Jesper Møller , Rasmus Waagepetersen

In this document we introduce a system model as the basis for a semantic model for UML 2.0. The system model is supposed to form the core and foundation of the UML semantics definition. For that purpose the basic system is targeted towards…

Software Engineering · Computer Science 2014-09-24 Manfred Broy , Maria Victoria Cengarle , Bernhard Rumpe

Spatial documentation is exponentially increasing given the availability of Big IoT Data, enabled by the devices miniaturization and data storage capacity. Bayesian spatial statistics is a useful statistical tool to determine the dependence…

Methodology · Statistics 2020-10-01 Francisco Louzada , Diego C. Nascimento , Osafu Augustine Egbon

This is an expository article for Elsevier's Encyclopedia of Mathematical Physics on the subject in the title. Comments/corrections welcome.

Exactly Solvable and Integrable Systems · Physics 2010-04-19 A. Doliwa , P. M. Santini

Probabilistic model checking is an approach to the formal modelling and analysis of stochastic systems. Over the past twenty five years, the number of different formalisms and techniques developed in this field has grown considerably, as…

Logic in Computer Science · Computer Science 2025-09-17 Marta Kwiatkowska , Gethin Norman , David Parker

Finite mixture of skew distributions have emerged as an effective tool in modelling heterogeneous data with asymmetric features. With various proposals appearing rapidly in the recent years, which are similar but not identical, the…

Methodology · Statistics 2013-05-29 Sharon X. Lee , Geoffrey J. McLachlan

In this note, we explore some recent advancements in enumerative algebraic geometry, focusing particularly on the role of quantum K-theory of quiver varieties as viewed through the lens of integrable systems. We highlight a number of…

Mathematical Physics · Physics 2024-12-30 Peter Koroteev

Originally published as a Supplemental Appendix to Adjoint Equations in Stability Analysis, Annu. Rev. Fluid Mech. 46:493-517 (2014)

Fluid Dynamics · Physics 2024-04-29 Paolo Luchini , Alessandro Bottaro

Many mechanical engineering applications call for multiscale computational modeling and simulation. However, solving for complex multiscale systems remains computationally onerous due to the high dimensionality of the solution space.…

Machine Learning · Computer Science 2023-03-23 Phong C. H. Nguyen , Joseph B. Choi , H. S. Udaykumar , Stephen Baek

Glass published the first report on the assessment of systems and software engineering scholars and institutions two decades ago. The ongoing, annual survey of publications in this field provides fund managers, young scholars, graduate…

Software Engineering · Computer Science 2014-07-21 Zhi Wang , Bing Li , Yutao Ma

This paper provides a tutorial discussion on analyzing structural equation modelling (SEM). SEM can be regarded as regression models with observed and unobserved indicators, have been extensively applied to practical and fundamental…

Methodology · Statistics 2015-04-15 Hashem Salarzadeh Jenatabadi

The recent progresses in Machine Learning opened the door to actual applications of learning algorithms but also to new research directions both in the field of Machine Learning directly and, at the edges with other disciplines. The case…

Disordered Systems and Neural Networks · Physics 2023-07-17 Aurélien Decelle

This is a survey on spectral theory of dynamical systems.

Dynamical Systems · Mathematics 2020-06-23 Adam Kanigowski , Mariusz Lemańczyk

In this article we focus on dynamic network data which describe interactions among a fixed population through time. We model this data using the latent space framework, in which the probability of a connection forming is expressed as a…

Methodology · Statistics 2021-12-21 Kathryn Turnbull , Christopher Nemeth , Matthew Nunes , Tyler McCormick

Statistical learning theory provides the theoretical basis for many of today's machine learning algorithms. In this article we attempt to give a gentle, non-technical overview over the key ideas and insights of statistical learning theory.…

Machine Learning · Statistics 2008-10-28 Ulrike von Luxburg , Bernhard Schoelkopf

The paper discusses a path-wise approach to stock price modelling.

Probability · Mathematics 2007-05-23 Rimas Norvaisa

Computational models pervade all branches of the exact sciences and have in recent times also started to prove to be of immense utility in some of the traditionally 'soft' sciences like ecology, sociology and politics. This volume is a…

For $ k \in \mathbb{N}$ we introduce an idempotent subalgebra, the spherical partition algebra ${\mathcal{SP} }_{k}$, of the partition algebra ${\mathcal{P} }_{k}$, that we define using an embedding associated with the trivial…

Representation Theory · Mathematics 2024-11-05 Katherine Ormeño Bastías , Paul Martin , Steen Ryom-Hansen