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Models can be simple for different reasons: because they yield a simple and computationally efficient interpretation of a generic dataset (e.g. in terms of pairwise dependences) - as in statistical learning - or because they capture the…

Disordered Systems and Neural Networks · Physics 2018-10-17 Alberto Beretta , Claudia Battistin , Clélia de Mulatier , Iacopo Mastromatteo , Matteo Marsili

In this paper we develop some combinatorial models for continuous spaces. In this spirit we study the approximations of continuous spaces by graphs, molecular spaces and coordinate matrices. We define the dimension on a discrete space by…

General Relativity and Quantum Cosmology · Physics 2009-10-22 Alexander V. Evako

In the present note we study combinatorial and algebraic properties of cubic-line arrangements in the complex projective plane admitting nodes, ordinary triple and $A_{5}$ singular points. We deliver a Hirzebruch-type inequality for such…

Algebraic Geometry · Mathematics 2024-03-27 Przemysław Talar

A well-known combinatorial algorithm can decide generic rigidity in the plane by determining if the graph is of Pollaczek-Geiringer-Laman type. Methods from matroid theory have been used to prove other interesting results, again under the…

Metric Geometry · Mathematics 2020-10-07 Andrew Frohmader , Alexander Heaton

Complex networks can be used to represent and model an ample diversity of abstract and real-world systems and structures. A good deal of the research on these structures has focused on specific topological properties, including node degree,…

Social and Information Networks · Computer Science 2023-11-08 Alexandre Benatti , Luciano da F. Costa

The moduli space of planar polygons with generic side lengths is a smooth, closed manifold. It is known that these manifolds contain the real points of the moduli space of distinct points on the projective line as an open dense subset.…

Algebraic Topology · Mathematics 2024-02-06 Navnath Daundkar , Priyavrat Deshpande

We characterise the embeddability of simply connected locally 3-connected 2-dimensional simplicial complexes in 3-space in a way analogous to Kuratowski's characterisation of graph planarity, by excluded minors. This answers questions of…

Combinatorics · Mathematics 2019-09-05 Johannes Carmesin

We give an elementary construction of symplectic connections through reduction. This provides an elegant description of a class of symmetric spaces and gives examples of symplectic connections with Ricci type curvature, which are not…

Symplectic Geometry · Mathematics 2007-05-23 P. Baguis , M. Cahen

We consider the construction of neural network architectures for data on simplicial complexes. In studying maps on the chain complex of a simplicial complex, we define three desirable properties of a simplicial neural network architecture:…

Machine Learning · Computer Science 2021-06-08 T. Mitchell Roddenberry , Nicholas Glaze , Santiago Segarra

Simplicial complexes can be viewed as high dimensional generalizations of graphs that explicitly encode multi-way ordered relations between vertices at different resolutions, all at once. This concept is central towards detection of higher…

Machine Learning · Computer Science 2022-07-05 Alexandros Dimitrios Keros , Vidit Nanda , Kartic Subr

A linear constraint system is specified by linear equations over the group $\ZZ_d$ of integers modulo $d$. Their operator solutions play an important role in the study of quantum contextuality and non-local games. In this paper, we use the…

Algebraic Topology · Mathematics 2023-05-16 Ho Yiu Chung , Cihan Okay , Igor Sikora

A symplectic structure on the space of nondegenerate and nonparametrized curves in a locally affine manifold is defined. We also consider several interesting spaces of nondegenerate projective curves endowed with Poisson structures. This…

High Energy Physics - Theory · Physics 2009-10-28 L. Guieu , V. Yu. Ovsienko

Generalized contact bundles are odd dimensional analogues of generalized complex manifolds. They have been introduced recently and very little is known about them. In this paper we study their local structure. Specifically, we prove a local…

Differential Geometry · Mathematics 2019-02-11 Jonas Schnitzer , Luca Vitagliano

We define a class of symplectic fibrations called symplectic configurations. They are natural generalization of Hamiltonian fibrations. Their geometric and topological properties are investigated. We are mainly concentrated on integral…

Symplectic Geometry · Mathematics 2010-05-13 Swiat Gal , Jarek Kedra

Let $Z$ be a projective hypersurface such that its underlying reduced variety has only isolated singularities. In case its irreducible components have constant multiplicities, for instance if $\dim Z>1$, we show that the spectrum of its…

Algebraic Geometry · Mathematics 2025-08-08 Seung-Jo Jung , Morihiko Saito , Youngho Yoon

In this note we show that in the simplicial setting, the classifying space construction converts short exact sequences of groups not just to homotopy fibrations, but in fact to fibre bundles.

Algebraic Topology · Mathematics 2025-07-04 Matthias Franz

We introduce the abstract notion of a closed necklical set in order to describe a functorial combinatorial model of the free loop fibration $\Omega Y\rightarrow \Lambda Y\rightarrow Y$ over the geometric realization $Y=|X|$ of a path…

Algebraic Topology · Mathematics 2018-08-20 Manuel Rivera , Samson Saneblidze

Configuration spaces of distinct labeled points on the plane are of practical relevance in designing safe control schemes for Automated Guided Vehicles (robots) in industrial settings. In this announcement, we consider the problem of the…

Geometric Topology · Mathematics 2007-05-23 Robert Ghrist

We consider the general model for dynamical systems defined on a simplicial complex. We describe the conjugacy classes of these systems and show how symmetries in a given simplicial complex manifest in the dynamics defined thereon,…

Dynamical Systems · Mathematics 2022-10-05 Eddie Nijholt , Lee DeVille

The major challenge in designing a discriminative learning algorithm for predicting structured data is to address the computational issues arising from the exponential size of the output space. Existing algorithms make different assumptions…

Machine Learning · Computer Science 2010-06-29 Shankar Vembu