Results 11 to 20 of about 3,761,116 (301)
GAIN: Graph Attention & Interaction Network for Inductive Semi-Supervised Learning Over Large-Scale Graphs [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2020 Graph Neural Networks (GNNs) have led to state-of-the-art performance on a variety of machine learning tasks such as recommendation, node classification and link prediction.
Yunpeng Weng +3 more
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Deep Graph Representation Learning and Optimization for Influence Maximization [PDF]
International Conference on Machine Learning, 2023 Influence maximization (IM) is formulated as selecting a set of initial users from a social network to maximize the expected number of influenced users. Researchers have made great progress in designing various traditional methods, and their theoretical ...
Chen Ling +7 more
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SimKGC: Simple Contrastive Knowledge Graph Completion with Pre-trained Language Models [PDF]
Annual Meeting of the Association for Computational Linguistics, 2022 Knowledge graph completion (KGC) aims to reason over known facts and infer the missing links. Text-based methods such as KGBERT (Yao et al., 2019) learn entity representations from natural language descriptions, and have the potential for inductive KGC ...
Liang Wang +3 more
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IEEE Access, 2023 Various graph neural networks (GNNs) have been proposed to solve node classification tasks in machine learning for graph data. GNNs use the structural information of graph data by aggregating the feature vectors of neighboring nodes.
Yuga Oishi, Ken Kaneiwa
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Taming Local Effects in Graph-based Spatiotemporal Forecasting [PDF]
Neural Information Processing Systems, 2023 Spatiotemporal graph neural networks have shown to be effective in time series forecasting applications, achieving better performance than standard univariate predictors in several settings.
Andrea Cini +3 more
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On cospectrality of gain graphs
Special Matrices, 2022 We define GG-cospectrality of two GG-gain graphs (Γ,ψ)\left(\Gamma ,\psi ) and (Γ′,ψ′)\left(\Gamma ^{\prime} ,\psi ^{\prime} ), proving that it is a switching isomorphism invariant.
Cavaleri Matteo, Donno Alfredo
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MGTAB: A Multi-Relational Graph-Based Twitter Account Detection Benchmark [PDF]
Neurocomputing, 2023 The development of social media user stance detection and bot detection methods rely heavily on large-scale and high-quality benchmarks. However, in addition to low annotation quality, existing benchmarks generally have incomplete user relationships ...
S. Shi +7 more
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Burnside Chromatic Polynomials of Group-Invariant Graphs
Discussiones Mathematicae Graph Theory, 2023 We introduce the Burnside chromatic polynomial of a graph that is invariant under a group action. This is a generalization of the Q-chromatic function Zaslavsky introduced for gain graphs.
White Jacob A.
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Domain Entity Extraction Method Based on Graph Sorting and Maximal Information Gain [PDF]
Jisuanji gongcheng, 2022 Domain knowledge graphs play an important role in various industries, and the acquisition of the domain entity is an important basis for their construction.However, existing approaches frequently rely on human work such as data annotation and the ...
ZHANG Xiaoming, ZHENG Lixin, WANG Huiyong
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On the Fractionalization of the Shift Operator on Graphs
IEEE Access, 2022 The theory of graph signal processing has been established with the purpose of generalizing tools from classical digital signal processing to the cases where the signal domain can be modeled by an arbitrary graph.
Guilherme B. Ribeiro +2 more
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