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Understanding and interacting with everyday physical scenes requires rich knowledge about the structure of the world, represented either implicitly in a value or policy function, or explicitly in a transition model. Here we introduce a new…

Through the subsequent discussion we consider a certain particular sort of (topological) algebras, which may substitute the `` structure sheaf algebras'' in many--in point of fact, in all--the situations of a geometrical character that…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Anastasios Mallios

Large scale models of physical phenomena demand the development of new statistical and computational tools in order to be effective. Many such models are `sloppy', i.e., exhibit behavior controlled by a relatively small number of parameter…

The initial motivation of this work was to give a topological interpretation of two-periodic twisted de-Rham cohomology which is generalizable to arbitrary coefficients. To this end we develop a sheaf theory in the context of locally…

Algebraic Topology · Mathematics 2012-10-12 Ulrich Bunke , Markus Spitzweck , Thomas Schick

Modellers of complex biological or social systems are often faced with an invidious choice: to use simple models with few mechanisms that can be fully analysed, or to construct complicated models that include all the features which are…

Physics and Society · Physics 2016-09-28 Luis F. Lafuerza , Louise Dyson , Bruce Edmonds , Alan J. McKane

Language is contextual and sheaf theory provides a high level mathematical framework to model contextuality. We show how sheaf theory can model the contextual nature of natural language and how gluing can be used to provide a global…

Computation and Language · Computer Science 2014-03-14 Samson Abramsky , Mehrnoosh Sadrzadeh

In naturalistic learning problems, a model's input contains a wide range of features, some useful for the task at hand, and others not. Of the useful features, which ones does the model use? Of the task-irrelevant features, which ones does…

Machine Learning · Computer Science 2020-10-26 Katherine L. Hermann , Andrew K. Lampinen

We introduce and study the notion of a locally proper map between topological spaces. We show that fundamental constructions of sheaf theory, more precisely proper base change, projection formula, and Verdier duality, can be extended from…

Algebraic Topology · Mathematics 2014-11-06 Olaf M. Schnürer , Wolfgang Soergel

Hierarchy is one of the most conspicuous features of numerous natural, technological and social systems. The underlying structures are typically complex and their most relevant organizational principle is the ordering of the ties among the…

Physics and Society · Physics 2014-03-05 Tamás Nepusz , Tamás Vicsek

If a Quillen model category can be specified using a certain logical syntax (intuitively, ``is algebraic/combinatorial enough''), so that it can be defined in any category of sheaves, then the satisfaction of Quillen's axioms over any site…

Category Theory · Mathematics 2009-11-07 Tibor Beke

This paper makes contributions to ``pure'' sheaf model theory, the part of model theory in which the models are sheaves over a complete Heyting algebra. We start by outlining the theory in a way we hope is readable for the non-specialist.…

Logic · Mathematics 2026-02-10 Andreas Brunner , Charles Morgan , Darllan Conceição Pinto

Networks have in recent years emerged as an invaluable tool for describing and quantifying complex systems in many branches of science. Recent studies suggest that networks often exhibit hierarchical organization, where vertices divide into…

Machine Learning · Statistics 2008-11-05 Aaron Clauset , Cristopher Moore , M. E. J. Newman

This paper outlines a program in what one might call spectral sheaf theory --- an extension of spectral graph theory to cellular sheaves. By lifting the combinatorial graph Laplacian to the Hodge Laplacian on a cellular sheaf of vector…

Algebraic Topology · Mathematics 2019-09-05 Jakob Hansen , Robert Ghrist

Many real-world systems studied are governed by complex, nonlinear dynamics. By modeling these dynamics, we can gain insight into how these systems work, make predictions about how they will behave, and develop strategies for controlling…

Machine Learning · Statistics 2019-06-05 Josue Nassar , Scott W. Linderman , Monica Bugallo , Il Memming Park

The topology of any complex system is key to understanding its structure and function. Fundamentally, algebraic topology guarantees that any system represented by a network can be understood through its closed paths. The length of each path…

Methodology · Statistics 2017-05-17 Pierre-André G. Maugis , Sofia C. Olhede , Patrick J. Wolfe

Complex systems are characterized by many interacting units that give rise to emergent behavior. A particularly advantageous way to study these systems is through the analysis of the networks that encode the interactions among the system's…

Physics and Society · Physics 2019-03-21 Alberto Aleta , Yamir Moreno

Several approaches to cognition and intelligence research rely on statistics-based models testing, namely factor analysis. In the present work we exploit the emerging dynamical systems perspective putting the focus on the role of the…

Physics and Society · Physics 2018-03-15 Gemma Rosell-Tarragó , Emanuele Cozzo , Albert Díaz-Guilera

In the present paper, we show how to construct an algebraic sheaf by means of the topological generalized group defined by Molaei in [16] by considering both homotopy and sheaf theory.

Algebraic Topology · Mathematics 2018-06-12 Hatice Aslan , Hakan Efe

The fundamental concept of applying the system methodology to network analysis declares that network architecture should take into account services and applications which this network provides and supports. This work introduces a formal…

Networking and Internet Architecture · Computer Science 2015-09-03 Andrey A. Shchurov

Mathematical models come in many forms across biological applications. In the case of complex, spatial dynamics and pattern formation, stochastic models also face two main challenges: pattern data is largely qualitative, and model…

Cell Behavior · Quantitative Biology 2022-12-26 Electa Cleveland , Angela Zhu , Bjorn Sandstede , Alexandria Volkening