Results 31 to 40 of about 337,199 (252)
Coloring problem of signed interval graphs [PDF]
Transactions on Combinatorics, 2019 A signed graph $(G,\sigma)$ is a graph together with an assignment of signs $\{+,-\}$ to its edges where $\sigma$ is the subset of its negative edges.
Farzaneh Ramezani
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Total Minimal Dominating Signed Graph [PDF]
, 2010 Cartwright and Harary considered graphs in which vertices represent persons and the edges represent symmetric dyadic relations amongst persons each of which designated as being positive or negative according to whether the nature of the relationship is ...
Reddy, Siva Kota, Vijay, S.
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On net-Laplacian energy of signed graphs
Communications in Combinatorics and Optimization, 2017 A signed graph is a graph where the edges are assigned either positive or negative signs. Net degree of a signed graph is the difference between the number of positive and negative edges incident with a vertex. It is said to be net-regular if all its
Nutan G. Nayak
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On Laplacian Equienergetic Signed Graphs [PDF]
Journal of Mathematics, 2021 The Laplacian energy of a signed graph is defined as the sum of the distance of its Laplacian eigenvalues from its average degree. Two signed graphs of the same order are said to be Laplacian equienergetic if their Laplacian energies are equal. In this paper, we present several infinite families of Laplacian equienergetic signed graphs.
Qingyun Tao, Lixin Tao
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Signed random walk diffusion for effective representation learning in signed graphs.
PLoS ONE, 2022 How can we model node representations to accurately infer the signs of missing edges in a signed social graph? Signed social graphs have attracted considerable attention to model trust relationships between people. Various representation learning methods
Jinhong Jung, Jaemin Yoo, U Kang
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Learning Weight Signed Network Embedding with Graph Neural Networks
Data Science and Engineering, 2023 Network embedding aims to map nodes in a network to low-dimensional vector representations. Graph neural networks (GNNs) have received much attention and have achieved state-of-the-art performance in learning node representation.
Zekun Lu +4 more
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Signed Graph Convolutional Networks
2018 IEEE International Conference on Data Mining (ICDM), 2018 Due to the fact much of today's data can be represented as graphs, there has been a demand for generalizing neural network models for graph data. One recent direction that has shown fruitful results, and therefore growing interest, is the usage of graph convolutional neural networks (GCNs). They have been shown to provide a significant improvement on a
Derr, Tyler, Ma, Yao, Tang, Jiliang
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A Study on Integer Additive Set-Valuations of Signed Graphs [PDF]
, 2015 Let $\N$ denote the set of all non-negative integers and $\cP(\N)$ be its power set. An integer additive set-labeling (IASL) of a graph $G$ is an injective set-valued function $f:V(G)\to \cP(\N)-\{\emptyset\}$ such that the induced function $f^+:E(G) \to
Germina, K. A., Sudev, N. K.
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Research on Extreme Signed Graphs with Minimal Energy in Tricyclic Signed Graphs S(n, n + 2)
Complexity, 2020 A signed graph is acquired by attaching a sign to each edge of a simple graph, and the signed graphs have been widely used as significant computer models in the study of complex systems.
Yajing Wang, Yubin Gao
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Signed Complete Graphs with Maximum Index
Discussiones Mathematicae Graph Theory, 2020 Let Γ = (G, σ) be a signed graph, where G is the underlying simple graph and σ E(G) → {−, +} is the sign function on the edges of G. The adjacency matrix of a signed graph has −1 or +1 for adjacent vertices, depending on the sign of the edges.
Akbari Saieed +3 more
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