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Conventional Knowledge Graph Completion (KGC) assumes that all test entities appear during training.
Holographic embeddings of knowledge graphs
Maximilian Nickel, Lorenzo Rosasco, and Tomaso A. Poggio. 2016 · 1961
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Open-world knowledge graph completion
Baoxu Shi and Tim Weninger. 2018 · 1964
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A three-way model for collective learning on multi-relational data
Maximilian Nickel, Volker Tresp, and Hans-Peter Kriegel. 2011 · 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 · 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 · 2013
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Knowledge graph embedding by translating on hyperplanes
Zhen Wang, Jianwen Zhang, Jianlin Feng, and Zheng Chen. 2014 · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2015 · 2015
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Learning entity and relation embeddings for knowledge graph completion
Yankai Lin, Zhiyuan Liu, Maosong Sun, Yang Liu, and Xuan Zhu. 2015 · 2015
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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 · 2015
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Representation learning of knowledge graphs with entity descriptions
Ruobing Xie, Zhiyuan Liu, Jia Jia, Huanbo Luan, and Maosong Sun. 2016 · 2016
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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 · 2017
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Image-embodied knowledge representation learning
TuckER: Tensor factorization for knowledge graph completion
Ivana Balazevic, Carl Allen, and Timothy M. Hospedales. 2019 · 2019
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RotatE: Knowledge graph embedding by relational rotation in complex space
Zhiqing Sun, Zhi-Hong Deng, Jian-Yun Nie, and Jian Tang. 2019 · 2019
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Logic attention based neighborhood aggregation for inductive knowledge graph embedding
Peifeng Wang, Jialong Han, Chenliang Li, and Rong Pan. 2019 · 2019
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Knowledge transfer for out-of-knowledge-base entities: Improving graph-neural-network-based embedding using convolutional layers
Zhongqin Bi, Tianchen Zhang, Ping Zhou, and Yongbin Li. 2020 · 2020
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Attention-based aggregation graph networks for knowledge graph information transfer
Ming Zhao, Weijia Jia, and Yusheng Huang. 2020 · 2020
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Ruobing Xie, Zhiyuan Liu, Huanbo Luan, and Maosong Sun. 2017 · 2017
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Théo Trouillon, Johannes Welbl, Sebastian Riedel, Éric Gaussier, and Guillaume Bouchard. 2016 · 2080
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