Results 41 to 50 of about 415,143 (70)
Gradient boosted graph convolutional network on heterophilic graph
Graph Neural Networks (GNNs) are impressive models that have been highly successful in performing graphical analysis and learning. However, GNNs are known to be outstanding in learning from homophilic graphs but are subpar in learning from heterophilic ...
Seah, Ming Yang
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Asymmetric game perfect graphs and the circular coloring game of weighted graphs [PDF]
, 2011 Zacharopoulos P. Asymmetric game perfect graphs and the circular coloring game of weighted graphs.
Zacharopoulos, Panagiotis
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Message Passing Neural Networks (MPNNs) have demonstrated remarkable success in node classification on homophilic graphs. It has been shown that they do not solely rely on homophily but on neighborhood distributions of nodes, i.e., consistency of the ...
Hoffmann, Marcel +2 more
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Heterophilic Graph Neural Networks Optimization with Causal Message-passing
In this work, we discover that causal inference provides a promising approach to capture heterophilic message-passing in Graph Neural Network (GNN).
Li, Jia +4 more
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Developments on Spectral Characterizations of Graphs [PDF]
In [E.R. van Dam and W.H. Haemers, Which graphs are determined by their spectrum?, Linear Algebra Appl. 373 (2003), 241-272] we gave a survey of answers to the question of which graphs are determined by the spectrum of some matrix associated to the graph.
Dam, E.R. van, Haemers, W.H.
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Dual-Frequency Filtering Self-aware Graph Neural Networks for Homophilic and Heterophilic Graphs
Graph Neural Networks (GNNs) have excelled in handling graph-structured data, attracting significant research interest. However, two primary challenges have emerged: interference between topology and attributes distorting node representations, and the ...
Wang, Shaofan +6 more
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Graph Neural Networks for Graphs With Heterophily: A Survey
Recent years have witnessed fast developments of graph neural networks (GNNs) that have benefited myriad graph analytic tasks and applications. Most GNNs rely on the homophily assumption that nodes belonging to the same class are more likely to be ...
Liu, Y +7 more
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Median computation in graphs using consensus strategies [PDF]
Following the Majority Strategy in graphs, other consensus strategies, namely Plurality Strategy, Hill Climbing and Steepest Ascent Hill Climbing strategies on graphs are discussed as methods for the computation of median sets of profiles.
Changat, M. +2 more
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An Odd Characterization of the Generalized Odd Graphs [PDF]
2010 Mathematics Subject Classification: 05E30, 05C50;distance-regular graphs;generalized odd graphs;odd-girth;spectra of graphs;spectral excess theorem;spectral ...
Dam, E.R. van, Haemers, W.H.
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Spectral Characterization of the Hamming Graphs [PDF]
We show that the Hamming graph H(3; q) with diameter three is uniquely determined by its spectrum for q ¸ 36. Moreover, we show that for given integer D ¸ 2, any graph cospectral with the Hamming graph H(D; q) is locally the disjoint union of D copies of
Koolen, J.H., Bang, S., Dam, E.R. van
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