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Numerous Graph Neural Networks (GNNs) have been developed to tackle the challenge of Knowledge Graph Embedding (KGE).
The expression of a tensor or a polyadic as a sum of products
Frank L. Hitchcock · 1927
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Some mathematical notes on three-mode factor analysis
Ledyard R Tucker · 1966
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Towards a standardized notation and terminology in multiway analysis
Henk A. L. Kiers · 2000
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A three-way model for collective learning on multi-relational data
Maximilian Nickel, Volker Tresp, and Hans-Peter Kriegel · 2011
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Translating embeddings for modeling multi-relational data
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko · 2013
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Reasoning with neural tensor networks for knowledge base completion
Richard Socher, Danqi Chen, Christopher D Manning, and Andrew Ng · 2013
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Knowledge graph embedding by translating on hyperplanes
Zhen Wang, Jianwen Zhang, Jianlin Feng, and Zheng Chen · 2014
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Embedding entities and relations for learning and inference in knowledge bases
Bishan Yang, Wen-tau Yih, Xiaodong He, Jianfeng Gao, and Li Deng · 2015
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Representing text for joint embedding of text and knowledge bases
Kristina Toutanova, Danqi Chen, Patrick Pantel, Hoifung Poon, Pallavi Choudhury, and Michael Gamon · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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Complex embeddings for simple link prediction
Théo Trouillon, Johannes Welbl, Sebastian Riedel, Éric Gaussier, and Guillaume Bouchard · 2016
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Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling · 2017
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Inductive representation learning on large graphs
Will Hamilton, Zhitao Ying, and Jure Leskovec · 2017
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Knowledge transfer for out-of-knowledge-base entities: A graph neural network approach
Takuo Hamaguchi, Hidekazu Oiwa, Masashi Shimbo, and Yuji Matsumoto · 2017
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Convolutional 2d knowledge graph embeddings
Tim Dettmers, Pasquale Minervini, Pontus Stenetorp, and Sebastian Riedel · 2018
Cited alongside, same era.
Modeling relational data with graph convolutional networks
Michael Schlichtkrull, Thomas N. Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, and Max Welling · 2018
Cited alongside, same era.
Canonical tensor decomposition for knowledge base completion
Timothee Lacroix, Nicolas Usunier, and Guillaume Obozinski · 2018
Cited alongside, same era.
Simple embedding for link prediction in knowledge graphs
Seyed Mehran Kazemi and David Poole · 2018
Cited alongside, same era.
Modeling polypharmacy side effects with graph convolutional networks
Marinka Zitnik, Monica Agrawal, and Jure Leskovec · 2018
Cited alongside, same era.
Graph attention networks
Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio · 2018
Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
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Low-dimensional hyperbolic knowledge graph embeddings
Ines Chami, Adva Wolf, Da-Cheng Juan, Frederic Sala, Sujith Ravi, and Christopher Ré · 2020
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Contextual parameter generation for knowledge graph link prediction
George Stoica, Otilia Stretcu, Emmanouil Antonios Platanios, Tom Mitchell, and Barnabás Póczos · 2020
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Inductive relation prediction by subgraph reasoning
Komal K. Teru, Etienne G. Denis, and William L. Hamilton · 2020
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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Cited alongside, same era.
Rotate: Knowledge graph embedding by relational rotation in complex space
Zhiqing Sun, Zhi-Hong Deng, Jian-Yun Nie, and Jian Tang · 2019
Cited alongside, same era.
Quaternion knowledge graph embeddings
SHUAI ZHANG, Yi Tay, Lina Yao, and Qi Liu · 2019
Cited alongside, same era.
Hypernetwork knowledge graph embeddings
Ivana Balažević, Carl Allen, and Timothy M. Hospedales · 2019
Cited alongside, same era.
End-to-end structure-aware convolutional networks for knowledge base completion
Chao Shang, Yun Tang, Jing Huang, Jinbo Bi, Xiaodong He, and Bowen Zhou · 2019
Cited alongside, same era.
Position-aware graph neural networks
Jiaxuan You, Rex Ying, and Jure Leskovec · 2019
Cited alongside, same era.
A2N: Attending to neighbors for knowledge graph inference
Trapit Bansal, Da-Cheng Juan, Sujith Ravi, and Andrew McCallum · 2019
Cited alongside, same era.
A re-evaluation of knowledge graph completion methods
Zhiqing Sun, Shikhar Vashishth, Soumya Sanyal, Partha Talukdar, and Yiming Yang · 2020
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Mixed-curvature multi-relational graph neural network for knowledge graph completion
Shen Wang, Xiaokai Wei, Cicero Nogueira Nogueira dos Santos, Zhiguo Wang, Ramesh Nallapati, Andrew Arnold, Bing Xiang, Philip S. Yu, and Isabel F. Cruz · 2021
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HittER: Hierarchical transformers for knowledge graph embeddings
Sanxing Chen, Xiaodong Liu, Jianfeng Gao, Jian Jiao, Ruofei Zhang, and Yangfeng Ji · 2021
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Eta prediction with graph neural networks in google maps
Austin Derrow-Pinion, Jennifer She, David Wong, Oliver Lange, Todd Hester, Luis Perez, Marc Nunkesser, Seongjae Lee, Xueying Guo, Brett Wiltshire, Peter W. Battaglia, Vishal Gupta, Ang Li, Zhongwen Xu, Alvaro Sanchez-Gonzalez, Yujia Li, and Petar Velickovic · 2021
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Modeling heterogeneous hierarchies with relation-specific hyperbolic cones
Yushi Bai, Zhitao Ying, Hongyu Ren, and Jure Leskovec · 2021
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Explainable GNN-based models over knowledge graphs
David Jaime Tena Cucala, Bernardo Cuenca Grau, Egor V. Kostylev, and Boris Motik · 2022
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Self-attention presents low-dimensional knowledge graph embeddings for link prediction
Peyman Baghershahi, Reshad Hosseini, and Hadi Moradi · 2023
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Indigo: Gnn-based inductive knowledge graph completion using pair-wise encoding
Shuwen Liu, Bernardo Grau, Ian Horrocks, and Egor Kostylev · 2045
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