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On understanding knowledge graph representation learning. Carl Allen, Ivana Balažević, Timothy M. Hospedales. [Paper]
Relation Embedding with Dihedral Group in Knowledge Graph. ACL 2019. Xu, Canran and Li, Ruijiang. [Paper]
RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space. ICLR 2019. Zhiqing Sun and Zhi-Hong Deng and Jian-Yun Nie and Jian Tang. [Paper] [Code]
Logic Attention Based Neighborhood Aggregation for Inductive Knowledge Graph Embedding. AAAI 2019. Wang, Peifeng and Han, Jialong and Li, Chenliang and Pan, Rong. [Paper]
Embedding Uncertain Knowledge Graphs. AAAI 2019. Chen et al. [Paper]
TransGate: Knowledge Graph Embedding with Shared Gate Structure. AAAI 2019. Yuan et al. [Paper]
Improved Knowledge Graph Embedding using Background Taxonomic Information. AAAI 2019. Fatemi et al. [Paper]
Validation of Growing Knowledge Graphs by Abductive Text Evidences. AAAI 2019. Du et al. [Paper]
Variational Quantum Circuit Model for Knowledge Graph Embedding. Advanced Quantum Technologies 2019. Yunpu Ma, Volker Tresp, Liming Zhao, and Yuyi Wang. [Paper]
Interaction Embeddings for Prediction and Explanation in Knowledge Graphs. WSDM 2019. Wen Zhang, Bibek Paudel, Wei Zhang, Abraham Bernstein, Huajun Chen. [Paper]
Does William Shakespeare Really Write Hamlet? Knowledge Representation Learning with Confidence. AAAI 2018. Ruobing Xie, Zhiyuan Liu, Fen Lin, and Leyu Lin. [Paper] [Code]
TorusE: Knowledge graph embedding on a lie group. AAAI 2018. Ebisu, Takuma and Ichise, Ryutaro. [Paper]
Convolutional 2d knowledge graph embeddings. AAAI 2018. Dettmers, Tim and Minervini, Pasquale and Stenetorp, Pontus and Riedel, Sebastian. [Paper]
Towards Understanding the Geometry of Knowledge Graph Embedding. ACL 2018. Chandrahas, Aditya Sharma and Partha Talukdar. [Paper] [Code] [Note]
Co-training Embedding of Knowledge Graphs and Entity Descriptions for Cross-lingual Entity Alignment. IJCAI 2018, Chen, Muhao, Yingtao Tian, Kai-Wei Chang, Steven Skiena, and Carlo Zaniolo. [Paper] [Note]
Scalable Rule Learning via Learning Representation. IJCAI 2018. Omran, Pouya Ghiasnezhad, Kewen Wang, and Zhe Wang. [Paper] [Note]
KBGAN: Adversarial Learning for Knowledge Graph Embeddings. NAACL 2018. Cai, Liwei, and William Yang Wang. [Paper] [Code] [Note]
Embedding Logical Queries on Knowledge Graphs. NIPS 2018. William L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, and Jure Leskovec. [Paper] [Code]
SimpIE Embedding for Link Prediction in Knowledge Graphs. NIPS 2018. Seyed Mehran Kazemi, David Poole. [Paper] [Code]
Differentiating Concepts and Instances for Knowledge Graph Embedding. EMNLP 2018. Xin Lv, Lei Hou, Juanzi Li, Zhiyuan Liu. [Paper] [Code]
Analogical inference for multi-relational embeddings. ICML 2017. Liu, Hanxiao and Wu, Yuexin and Yang, Yiming. [Paper] [Code]
Poincaré embeddings for learning hierarchical representations. NIPS 2017. Nickel, Maximillian and Kiela.[Paper] [Code]
On the equivalence of holographic and complex embeddings for link prediction. ACL 2017. Hayashi, Katsuhiko and Shimbo, Masashi. [Paper]
Modeling relational data with graph convolutional networks. European Semantic Web Conference 2017. Schlichtkrull, Michael and Kipf, Thomas N and Bloem, Peter and Van Den Berg, Rianne and Titov, Ivan and Welling, Max. [Paper]
Holographic embeddings of knowledge graphs. AAAI 2016. Nickel, Maximilian and Rosasco, Lorenzo and Poggio, Tomaso. [Paper]
Complex embeddings for simple link prediction. ICML 2016. Trouillon, Théo and Welbl, Johannes and Riedel, Sebastian and Gaussier, Éric and Bouchard, Guillaume. [Paper] [Code]
Embedding entities and relations for learning and inference in knowledge bases. ICLR 2015. Yang, Bishan and Yih, Wen-tau and He, Xiaodong and Gao, Jianfeng and Deng, Li. [Paper]
Effective blending of two and three-way interactions for modeling multi-relational data. ECML-KDD 2014. García-Durán, Alberto and Bordes, Antoine and Usunier, Nicolas. [Paper]
Relation extraction with matrix factorization and universal schemas. NAACL 2013. Riedel, Sebastian and Yao, Limin and McCallum, Andrew and Marlin, Benjamin M. [Paper]
A latent factor model for highly multi-relational data. NIPS 2012. Jenatton, Rodolphe and Roux, Nicolas L and Bordes, Antoine and Obozinski, Guillaume R. [Paper]
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Knowledge graph embedding by translating on hyperplanes. AAAI 2014. Wang, Zhen and Zhang, Jianwen and Feng, Jianlin and Chen, Zheng. [Paper]
Learning entity and relation embeddings for knowledge graph completion. AAAI 2015. Lin, Yankai and Liu, Zhiyuan and Sun, Maosong and Liu, Yang and Zhu, Xuan. [Paper] [Code]
STransE: a novel embedding model of entities and relationships in knowledge bases. NAACL 2016. Nguyen, Dat Quoc and Sirts, Kairit and Qu, Lizhen and Johnson, Mark. [Paper]
Knowledge graph embedding via dynamic mapping matrix. ACL 2015. Ji, Guoliang and He, Shizhu and Xu, Liheng and Liu, Kang and Zhao, Jun. [Paper]
A translation-based knowledge graph embedding preserving logical property of relations. NAACL 2016. Yoon, Hee-Geun and Song, Hyun-Je and Park, Seong-Bae and Park, Se-Young. [Paper]
Knowledge graph completion with adaptive sparse transfer matrix. AAAI 2016. Ji, Guoliang and Liu, Kang and He, Shizhu and Zhao, Jun. [Paper]
TransA: An adaptive approach for knowledge graph embedding. AAAI 2015. Xiao, Han and Huang, Minlie and Hao, Yu and Zhu, Xiaoyan. [Paper]
Knowledge graph embedding by flexible translation. KR 2016. Feng, Jun and Huang, Minlie and Wang, Mingdong and Zhou, Mantong and Hao, Yu and Zhu, Xiaoyan. [Paper]
Learning to represent knowledge graphs with gaussian embedding. CIKM 2015. He, Shizhu and Liu, Kang and Ji, Guoliang and Zhao, Jun. [Paper]
From one point to a manifold: Orbit models for knowledge graph embedding. IJCAI 2016. Xiao, Han and Huang, Minlie and Zhu, Xiaoyan. [Paper]
Composing relationships with translations. EMNLP 2015. García-Durán, Alberto and Bordes, Antoine and Usunier, Nicolas. [Paper] [Code]
A semantic matching energy function for learning with multi-relational data. Machine Learning 2014. Bordes, Antoine and Glorot, Xavier and Weston, Jason and Bengio, Yoshua. [Paper]