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Knowledge graph embedding research has overlooked the problem of probability calibration.
Verification of forecasts expressed in terms of probability
Glenn W Brier · 1950
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Holographic embeddings of knowledge graphs
Maximilian Nickel, Lorenzo Rosasco, Tomaso A Poggio, et al · 1961
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The comparison and evaluation of forecasters
Morris H DeGroot and Stephen E Fienberg · 1983
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Knowledge graph embedding with hierarchical relation structure
Zhao Zhang, Fuzhen Zhuang, Meng Qu, Fen Lin, and Qing He · 1983
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Wordnet: a lexical database for english
George A Miller · 1995
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Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods
John Platt et al · 1999
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Transforming classifier scores into accurate multiclass probability estimates
Bianca Zadrozny and Charles Elkan · 2002
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Predicting good probabilities with supervised learning
Alexandru Niculescu-Mizil and Rich Caruana · 2005
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Freebase: a collaboratively created graph database for structuring human knowledge
Kurt Bollacker, Colin Evans, Praveen Paritosh, Tim Sturge, and Jamie Taylor · 2008
Earlier work this paper cites.
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
Earlier work this paper cites.
Yago3: A knowledge base from multilingual wikipedias
Farzaneh Mahdisoltani, Joanna Biega, and Fabian M Suchanek · 2013
Earlier work this paper cites.
Reasoning with neural tensor networks for knowledge base completion
Richard Socher, Danqi Chen, Christopher D Manning, and Andrew Ng · 2013
Earlier work this paper cites.
Knowledge vault: A web-scale approach to probabilistic knowledge fusion
Xin Dong, Evgeniy Gabrilovich, Geremy Heitz, Wilko Horn, Ni Lao, Kevin Murphy, Thomas Strohmann, Shaohua Sun, and Wei Zhang · 2014
Earlier work this paper cites.
Learning to represent knowledge graphs with gaussian embedding
Shizhu He, Kang Liu, Guoliang Ji, and Jun Zhao · 2015
Cited alongside, same era.
Ensemble solutions for link-prediction in knowledge graphs
Denis Krompaß and Volker Tresp · 2015
Cited alongside, same era.
Obtaining well calibrated probabilities using bayesian binning
Mahdi Pakdaman Naeini, Gregory Cooper, and Milos Hauskrecht · 2015
Cited alongside, same era.
Representing text for joint embedding of text and knowledge bases
Kristina Toutanova, Danqi Chen, Patrick Pantel, Hoifung Poon, Pallavi Choudhury, and Michael Gamon · 2015
Cited alongside, same era.
Embedding entities and relations for learning and inference in knowledge bases
Bishan Yang, Scott Wen-tau Yih, Xiaodong He, Jianfeng Gao, and Li Deng · 2015
Cited alongside, same era.
Tensorflow: A system for large-scale machine learning
Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, et al · 2016
Kbgan: Adversarial learning for knowledge graph embeddings
Liwei Cai and William Yang Wang · 2018
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Convolutional 2d knowledge graph embeddings
Tim Dettmers, Pasquale Minervini, Pontus Stenetorp, and Sebastian Riedel · 2018
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Toruse: Knowledge graph embedding on a lie group
Takuma Ebisu and Ryutaro Ichise · 2018
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Simple embedding for link prediction in knowledge graphs
Seyed Mehran Kazemi and David Poole · 2018
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Accurate uncertainties for deep learning using calibrated regression
Volodymyr Kuleshov, Nathan Fenner, and Stefano Ermon · 2018
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Canonical tensor decomposition for knowledge base completion
Timothee Lacroix, Nicolas Usunier, and Guillaume Obozinski · 2018
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Knowledge graph completion with adaptive sparse transfer matrix
Guoliang Ji, Kang Liu, Shizhu He, and Jun Zhao · 2016
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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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A comprehensive survey of graph embedding: Problems, techniques and applications
Hongyun Cai, Vincent W Zheng, and Kevin Chen-Chuan Chang · 2017
Cited alongside, same era.
On calibration of modern neural networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q Weinberger · 2017
Cited alongside, same era.
Knowledge transfer for out-of-knowledge-base entities: a graph neural network approach
Takuo Hamaguchi, Hidekazu Oiwa, Masashi Shimbo, and Yuji Matsumoto · 2017
Cited alongside, same era.
Analysis of the impact of negative sampling on link prediction in knowledge graphs
Bhushan Kotnis and Vivi Nastase · 2017
Cited alongside, same era.
Later among the works it cites.
Differentiating concepts and instances for knowledge graph embedding
Xin Lv, Lei Hou, Juanzi Li, and Zhiyuan Liu · 2018
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A novel embedding model for knowledge base completion based on convolutional neural network
Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, and Dinh Phung · 2018
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Tucker: Tensor factorization for knowledge graph completion
Ivana Balažević, Carl Allen, and Timothy M Hospedales · 2019
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AmpliGraph: a Library for Representation Learning on Knowledge Graphs, March 2019
Luca Costabello, Sumit Pai, Chan Le Van, Rory McGrath, Nicholas McCarthy, and Pedro Tabacof · 2019
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Learning attention-based embeddings for relation prediction in knowledge graphs
Deepak Nathani, Jatin Chauhan, Charu Sharma, and Manohar Kaul · 2019
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A capsule network-based embedding model for knowledge graph completion and search personalization
Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dat Quoc Nguyen, and Dinh Phung · 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
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Quaternion knowledge graph embedding
Shuai Zhang, Yi Tay, Lina Yao, and Qi Liu · 2019
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