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This paper builds on the connection between graph neural networks and traditional dynamical systems. We propose continuous graph neural networks (CGNN), which generalise existing graph neural networks with discrete dynamics in that they can…

Machine Learning · Computer Science 2020-07-17 Louis-Pascal A. C. Xhonneux , Meng Qu , Jian Tang

We prove a formula for a characteristic polynomial of an operator expressed as a polynomial of rank 1 operators. The formula uses a discrete analog of path integration and implies a generalization of the Forman-Kenyon's formula [4,6] for a…

Combinatorics · Mathematics 2012-09-11 Yurii M. Burman

We present a new feature extraction method for complex and large datasets, based on the concept of transport operators on graphs. The proposed approach generalizes and extends the many existing data representation methodologies built upon…

Machine Learning · Computer Science 2019-11-01 Wojciech Czaja , Dong Dong , Pierre-Emmanuel Jabin , Franck Olivier Ndjakou Njeunje

We study invariants of virtual graphoids, which are virtual spatial graph diagrams with two distinguished degree-one vertices modulo graph Reidemeister moves applied away from the distinguished vertices. Generalizing previously known…

Combinatorics · Mathematics 2022-09-20 Neslihan Gügümcü , Louis H. Kauffman , Puttipong Pongtanapaisan

One exact and two heuristic algorithms for determining the generators, orbits and order of the graph automorphism group are presented. A basic tool of these algorithms is the well-known individualization and refinement procedure. A search…

Data Structures and Algorithms · Computer Science 2016-07-27 Stoicho D. Stoichev

Operator learning has been highly successful for continuous mappings between infinite-dimensional spaces, such as PDE solution operators. However, many operators of interest-including differential operators-are discontinuous or set-valued,…

Machine Learning · Computer Science 2026-05-13 Takashi Furuya , Yury Korolev , Takaharu Yaguchi

For a family of Jacobians of smooth pointed curves there is a notion of tautological algebra. There is an action of $\mathfrak{sl}_2$ on this algebra. We define and study a lifting of the Polishchuk operator, corresponding to $f\in…

Algebraic Geometry · Mathematics 2019-04-17 Gabriel C. Drummond-Cole , Mehdi Tavakol

We introduce a convolutional neural network that operates directly on graphs. These networks allow end-to-end learning of prediction pipelines whose inputs are graphs of arbitrary size and shape. The architecture we present generalizes…

Navigating topological transitions in cellular mechanical systems is a significant challenge for existing simulation methods. While abstract models lack predictive capabilities at the cellular level, explicit network representations…

Graphics · Computer Science 2024-04-30 Logan Numerow , Yue Li , Stelian Coros , Bernhard Thomaszewski

Distributed order fractional operators offer a rigorous tool for mathematical modelling of multi-physics phenomena, where the differential orders are distributed over a range of values rather than being just a fixed integer/fraction as it…

Numerical Analysis · Mathematics 2016-05-02 Ehsan Kharazmi , Mohsen Zayernouri , George Em Karniadakis

In this dissertation, we explore the structure of inversion graphs of permutations--a class of graphs that naturally arises by representing each permutation as a graph, where vertices correspond to entries and edges encode inversions.…

Combinatorics · Mathematics 2025-06-30 Sean Mandrick

We consider $2p\ge 4$ order differential operator on the real line with a periodic coefficients. The spectrum of this operator is absolutely continuous and is a union of spectral bands separated by gaps. We define the Lyapunov function,…

Mathematical Physics · Physics 2010-10-07 Andrey Badanin , Evgeny Korotyaev

We construct a natural chain map from the Kontsevich graph complex to the rational singular chain complex of $B\mathrm{Diff}_\partial(D^{2k})$ when the dimension $2k$ is sufficiently large, generalizing Goussarov and Habiro's theories of…

Geometric Topology · Mathematics 2026-01-14 Boris Botvinnik , Tadayuki Watanabe

The question of self-adjoint realizations of sign-indefinite second order differential operators is discussed in terms of a model problem. Operators of the type $-\frac{d}{dx} \sgn (x) \frac{d}{dx}$ are generalized to finite, not…

Mathematical Physics · Physics 2021-03-29 Amru Hussein

We propose an approach to learning with graph-structured data in the problem domain of graph classification. In particular, we present a novel type of readout operation to aggregate node features into a graph-level representation. To this…

Machine Learning · Computer Science 2021-05-18 Christoph D. Hofer , Florian Graf , Bastian Rieck , Marc Niethammer , Roland Kwitt

In this paper we introduced an arithmetic graph function which associates with every group G the directed graph whose vertices corresponds to the divisors of |G|. With the help of such functions we introduced arithmetic graphs of classes of…

Group Theory · Mathematics 2015-10-14 V. I. Murashka , A. F. Vasil'ev

We discuss ways in which momentum operators can be introduced on an oriented metric graph. A necessary condition appears to the balanced property, or a matching between the numbers of incoming and outgoing edges; we show that a graph…

Mathematical Physics · Physics 2020-02-07 Pavel Exner

We show that 2D periodic operators with local and perpendicular defects form an algebra. We provide an algorithm of finding spectrum for such operators. While the continuous spectral components can be computed by simple algebraic operations…

Spectral Theory · Mathematics 2016-06-07 Anton A. Kutsenko

In this brief note, we report a formal mathematical observation: we are about to breach a major century-old barrier in the analysis of interacting particle systems. More precisely, it is well-known that in…

Adaptation and Self-Organizing Systems · Physics 2020-06-24 Christian Kuehn

We study the tailoring of structured random graph ensembles to real networks, with the objective of generating precise and practical mathematical tools for quantifying and comparing network topologies macroscopically, beyond the level of…

Disordered Systems and Neural Networks · Physics 2015-05-13 A. Annibale , A. C. C. Coolen , L. P. Fernandes , F. Fraternali , J. Kleinjung