Results 51 to 60 of about 6,572,416 (223)
GAPointNet: Graph attention based point neural network for exploiting local feature of point cloud
Neurocomputing, 2021 Exploiting ο¬ne-grained semantic features on point cloud data is still challenging because of its irregular and sparse structure in a non-Euclidean space.
Can Chen +2 more
semanticscholar +1 more source
TMGAT:Graph Attention Network with Type Matching Constraint [PDF]
Jisuanji kexueThe graph structure has recently been employed to solve the KGC problem of knowledge graph completion.The graph neural network(GNNs) constantly updates the representation of the central entity by aggregating the entity's local neighborhood information ...
SUN Shounan, WANG Jingbin, WU Renfei, YOU Changkai, KE Xifan, HUANG Hao
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Discussiones Mathematicae Graph Theory, 2015 Erratum Identification and corrections of the existing mistakes in the paper On the total graph of Mycielski graphs, central graphs and their covering numbers, Discuss. Math. Graph Theory 33 (2013) 361-371.
Forouhandeh S.F. +4 more
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Mapping graph state orbits under local complementation [PDF]
Quantum, 2020 Graph states, and the entanglement they posses, are central to modern quantum computing and communications architectures. Local complementation β the graph operation that links all local-Clifford equivalent graph states β allows us to classify all ...
Jeremy C. Adcock +3 more
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Betweenness centrality in Cartesian product of graphs [PDF]
AKCE International Journal of Graphs and Combinatorics, 2017 Betweenness centrality is a widely-used measure in the analysis of large complex networks. It measures the potential or power of a vertex to control the communication over the network under the assumption that information primarily flows over the shortest paths between them.
Sunil Kumar R., Kannan Balakrishnan
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Spike-based graph centrality measures [PDF]
International Conference on Neuromorphic Systems 2020, 2020 We derive several spike-based routines that compute or establish bounds on radial centrality measures for undirected graphs and trees without the use of matrix multiplication. These spike-based centrality measures utilize a direct embedding of graph nodes and edges into neurons and synapses, can be implemented with static synapses or plastic synapses ...
Kathleen Hamilton +3 more
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RAGAT: Relation Aware Graph Attention Network for Knowledge Graph Completion
IEEE Access, 2021 Knowledge graph completion (KGC) is the task of predicting missing links based on known triples for knowledge graphs. Several recent works suggest that Graph Neural Networks (GNN) that exploit graph structures achieve promising performance on KGC.
Xiyang Liu +3 more
semanticscholar +1 more source
Experimental entanglement of six photons in graph states [PDF]
, 2006 Graph states are special kinds of multipartite entangled states that correspond to mathematical graphs where the vertices take the role of quantum spin systems and the edges represent interactions.
Gao, Wei-Bo +8 more
core +3 more sources
A note on star coloring of central graph of bipartite graph and corona graph of complete graph with path and cycle [PDF]
Transactions on Combinatorics, 2012 In this paper, we find the star chromatic number of central graph of complete bipartite graph and corona graph of complete graph with path and cycle.
V. J. Vernold, M. Venkatachalam
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Equitable Coloring on Total Graph of Bigraphs and Central Graph of Cycles and Paths
International Journal of Mathematics and Mathematical Sciences, 2011 The notion of equitable coloring was introduced by Meyer in 1973. In this paper we obtain interesting results regarding the equitable chromatic number π= for the total graph of complete bigraphs π(πΎπ,π), the central graph of cycles πΆ(πΆπ) and the central ...
J. Vernold Vivin +2 more
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