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Showing 1 to 6 of 6 for “"Representations of graphs"”.

  1. Intersection representations of graphs and digraphs

    … if and only if its adjacency matrix is free of six forbidden submatrices: three 3 by 4 matrices and their transposes.

    uiuc Repository record for Intersection representations of graphs and digraphs (opens in a new tab)

  2. Continued fractions and representations of graphs

    Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2020-08-25 without embargo terms

    uiuc Repository record for Continued fractions and representations of graphs (opens in a new tab)

  3. On local representations of graphs and networks

    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 1993.

    mit Repository record for On local representations of graphs and networks (opens in a new tab)

  4. On a graph parameter related to vertex labelings and its application to minimum rank problems in graph theory

    … rank and minimum positive semidefinite rank of a simple graph. A graph parameter, called the minimum labeling degree (mld), is defined in terms of the concept of a vertex labeling of a graph, and its value is calculated for a few graph classes. It is proved here that there is a conception of

    utc Repository record for On a graph parameter related to vertex labelings and its application to minimum rank problems in graph theory (opens in a new tab)

  5. Equilibrium graphs on the flat torus or finding zen amidst the bull

    … spring embedding theorem, and equilibrium graphs on the plane in general, have been a subject of study for many decades, with connections to and applications in many areas, including, but not limited to, discrete geometry, planar graph theory, graphics, surface parametrization, mechanical …

    uiuc Repository record for Equilibrium graphs on the flat torus or finding zen amidst the bull (opens in a new tab)

  6. Distributional and relational inductive biases for graph representation learning in biomedicine

    … life processes motivates the mass collection of biomolecular data and data-driven modelling to gain insights into physiological phenomena. Recent predictive modelling efforts have focused on deep representation learning methods which offer a flexible modelling paradigm to handling high …

    cambridge Repository record for Distributional and relational inductive biases for graph representation learning in biomedicine (opens in a new tab)