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Many papers have been published on the knowledge base completion task in the past few years.
Holographic Embeddings of Knowledge Graphs
Maximilian Nickel, Lorenzo Rosasco, and Tomaso Poggio. 2016 · 1961
Earlier work this paper cites.
A direct adaptive method for faster backpropagation learning: The rprop algorithm
Martin Riedmiller and Heinrich Braun. 1993 · 1993
Earlier work this paper cites.
Freebase: A collaboratively created graph database for structuring human knowledge
Kurt Bollacker, Colin Evans, Praveen Paritosh, Tim Sturge, and Jamie Taylor. 2008 · 2008
Earlier work this paper cites.
Learning structured embeddings of knowledge bases
Antoine Bordes, Jason Weston, Ronan Collobert, and Yoshua Bengio. 2011 · 2011
Earlier work this paper cites.
Translating embeddings for modeling multi-relational data
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko. 2013 · 2013
Earlier work this paper cites.
Reasoning With Neural Tensor Networks for Knowledge Base Completion
Richard Socher, Danqi Chen, Christopher D. Manning, and Andrew Y. Ng. 2013 · 2013
Earlier work this paper cites.
A semantic matching energy function for learning with multi-relational data
Antoine Bordes, Xavier Glorot, Jason Weston, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Knowledge Graph Embedding by Translating on Hyperplanes
Zhen Wang, Jianwen Zhang, Jianlin Feng, and Zheng Chen. 2014 · 2014
Earlier work this paper cites.
TensorFlow : Large-Scale Machine Learning on Heterogeneous Distributed Systems
Martin Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Man, Rajat Monga, Sherry Moore, Derek Murray, Jon Shlens, Benoit Steiner, Ilya Sutskever, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Oriol Vinyals, Pete Warden, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng. 2015 · 2015
Earlier work this paper cites.
Keras https://github.com/fchollet/keras/
Francois Chollet. 2015 · 2015
Earlier work this paper cites.
GAKE: Graph Aware Knowledge Embedding
Jun Feng, Minlie Huang, Yang Yang, and Xiaoyan Zhu. 2015 · 2015
Earlier work this paper cites.
Composing Relationships with Translations
Alberto García-Durán, Antoine Bordes, and Nicolas Usunier. 2015 · 2015
Earlier work this paper cites.
Learning to Represent Knowledge Graphs with Gaussian Embedding
Shizhu He, Kang Liu, Guoliang Ji, and Jun Zhao. 2015 · 2015
Cited alongside, same era.
Knowledge Graph Embedding via Dynamic Mapping Matrix
Guoliang Ji, Shizhu He, Liheng Xu, Kang Liu, and Jun Zhao. 2015 · 2015
Cited alongside, same era.
Adam: a Method for Stochastic Optimization
Diederik P. Kingma and Jimmy Lei Ba. 2015 · 2015
Cited alongside, same era.
Improving Distributional Similarity with Lessons Learned from Word Embeddings
Omer Levy, Yoav Goldberg, and Ido Dagan. 2015 · 2015
Cited alongside, same era.
A Review of Relational Machine Learning for Knowledge Graph
Maximilian Nickel, Kevin Murphy, Volker Tresp, and Evgeniy Gabrilovich. 2015 · 2015
Cited alongside, same era.
Observed versus latent features for knowledge base and text inference
Kristina Toutanova and Danqi Chen. 2015 · 2015
Implicit reasonet: Modeling large-scale structured relationships with shared memory
Yelong Shen, Po-Sen Huang, Ming-Wei Chang, and Jianfeng Gao. 2016 · 2016
Later among the works it cites.
Text-enhanced representation learning for knowledge graph
Zhigang Wang and Juanzi Li. 2016 · 2016
Later among the works it cites.
A Translation-Based Knowledge Graph Embedding Preserving Logical Property of Relations
Hee-geun Yoon, Hyun-je Song, Seong-bae Park, and Se-young Park. 2016 · 2016
Later among the works it cites.
Emerging trends: I did it, I did it, I did it, but. .
Kenneth Ward Church. 2017 · 2017
Closest in time.
Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks
Rajarshi Das, Arvind Neelakantan, David Belanger, and Andrew Mccallum. 2017 · 2017
Closest in time.
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Cited alongside, same era.
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
Cited alongside, same era.
Combining Two And Three-Way Embeddings Models for Link Prediction in Knowledge Bases
Alberto Garcia-Duran, Antoine Bordes, Nicolas Usunier, and Yves Grandvalet. 2016 · 2016
Cited alongside, same era.
Knowledge Graph Completion with Adaptive Sparse Transfer Matrix
Guoliang Ji, Kang Liu, Shizhu He, and Jun Zhao. 2016 · 2016
Cited alongside, same era.
Hierarchical random walk inference in knowledge graphs
Qiao Liu, Liuyi Jiang, Minghao Han, Yao Liu, and Zhiguang Qin. 2016 · 2016
Cited alongside, same era.
STransE: a novel embedding model of entities and relationships in knowledge bases
Dat Quoc Nguyen, Kairit Sirts, Lizhen Qu, and Mark Johnson. 2016 · 2016
Cited alongside, same era.
Discriminative gaifman models
Mathias Niepert. 2016 · 2016
Cited alongside, same era.
Katsuhiko Hayashi and Masashi Shimbo. 2017 · 2017
Closest in time.
Dat Quoc Nguyen. 2017 · 2017
Closest in time.
Modeling Relational Data with Graph Convolutional Networks http://arxiv.org/abs/1703.06103
Michael Schlichtkrull, Thomas N. Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, and Max Welling. 2017 · 2017
Closest in time.
ProjE : Embedding Projection for Knowledge Graph Completion
Baoxu Shi and Tim Weniger. 2017 · 2017
Closest in time.
Knowledge Graph Completion via Complex Tensor Factorization http://arxiv.org/abs/1702.06879
Théo Trouillon, Christopher R. Dance, Johannes Welbl, Sebastian Riedel, Éric Gaussier, and Guillaume Bouchard. 2017 · 2017
Closest in time.
Ssp: Semantic space projection for knowledge graph embedding with text descriptions
Han Xiao, Minlie Huang, and Xiaoyan Zhu. 2017 · 2017
Closest in time.
Complex Embeddings for Simple Link Prediction
Théo Trouillon, Johannes Welbl, Sebastian Riedel, Eric Gaussier, and Guillaume Bouchard. 2016 · 2080
Closest in time.