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Graph Representation Learning in Document Wikification
2021Wikification (entity annotation) is a challenging task in Natural Language Processing (NLP). It is a method to automatically enrich a text with links to Wikipedia as a knowledge base. Wikification starts from detecting ambiguous mentions in the document, and later tries to disambiguate those mentions.
Mozhgan Saeidi +2 more
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Representation Learning on Graphs
2018The primary challenge of applying machine learning in graph theory is finding a way to represent, or encode, graph structure so that it can be easily exploited by machine learning models. Traditionally, machine learning approaches relied on user-defined heuristics to extract features encoding structural information about a graph.
Krishna Raj P. M. +2 more
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Graph explicit pooling for graph-level representation learning
Neural NetworksGraph pooling has been increasingly recognized as crucial for Graph Neural Networks (GNNs) to facilitate hierarchical graph representation learning. Existing graph pooling methods commonly consist of two stages: selecting top-ranked nodes and discarding the remaining to construct coarsened graph representations.
Chuang Liu 0008 +7 more
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AGCL: Adaptive Graph Contrastive Learning for graph representation learning
Neurocomputing, 2023Jiajun Yu, Adele Lu Jia
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Graph representation learning in bioinformatics: trends, methods and applications
Briefings in Bioinformatics, 2022Hai-Cheng Yi +2 more
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Unsupervised graph-level representation learning with hierarchical contrasts
Neural Networks, 2023Huasong Zhong, Xiao Luo, Wei Ju
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Graph-Guided Unsupervised Multiview Representation Learning
IEEE Transactions on Circuits and Systems for Video Technology, 2023Jihua Zhu, Qinghai Zheng, Haoyu Tang
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A Novel Representation Learning for Dynamic Graphs Based on Graph Convolutional Networks
IEEE Transactions on Cybernetics, 2023Zhen Wang, Chao Gao, Zhen Wang
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CommPOOL: An interpretable graph pooling framework for hierarchical graph representation learning
Neural Networks, 2021Lifang He, Heng Huang, Liang Zhan
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