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Research on link prediction in knowledge graphs has mainly focused on static multi-relational data.
Dropout: A simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2014 · 1958
Earlier work this paper cites.
Handbook of logic in artificial intelligence and logic programming (vol. 4)
J. van Benthem. 1995 · 1995
Earlier work this paper cites.
Visualizing data using t-sne
Laurens van der Maaten and Geoffrey Hinton. 2008 · 2008
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.
A temporal-probabilistic database model for information extraction
Maximilian Dylla, Iris Miliaraki, and Martin Theobald. 2013 · 2013
Earlier work this paper cites.
Yago2: A spatially and temporally enhanced knowledge base from wikipedia
Johannes Hoffart, Fabian M Suchanek, Klaus Berberich, and Gerhard Weikum. 2013 · 2013
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
Earlier work this paper cites.
Learning multi-relational semantics using neural-embedding models
Bishan Yang, Wen-tau Yih, Xiaodong He, Jianfeng Gao, and Li Deng. 2014 · 2014
Cited alongside, same era.
Traversing knowledge graphs in vector space
Kelvin Guu, John Miller, and Percy Liang. 2015 · 2015
Cited alongside, same era.
Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015 · 2015
Cited alongside, same era.
Predicting the co-evolution of event and knowledge graphs
C. Esteban, V. Tresp, Y. Yang, S. Baier, and D. Krompaß. 2016 · 2016
Cited alongside, same era.
Towards time-aware knowledge graph completion
Tingsong Jiang, Tian Yu Liu, Tao Ge, Lei Sha, Baobao Chang, Sujian Li, and Zhifang Sui. 2016 · 2016
Cited alongside, same era.
Marrying uncertainty and time in knowledge graphs
Melisachew Wudage Chekol, Giuseppe Pirrò, Joerg Schoenfisch, and Heiner Stuckenschmidt. 2017 · 2017
Later among the works it cites.
Rule Based Temporal Inference
Melisachew Wudage Chekol and Heiner Stuckenschmidt. 2018 · 2017
Later among the works it cites.
Alberto Garcia-Duran and Mathias Niepert. 2017 · 2017
Later among the works it cites.
Knowledge base completion: Baselines strike back
Rudolf Kadlec, Ondrej Bajgar, and Jan Kleindienst. 2017 · 2017
Later among the works it cites.
Know-evolve: Deep temporal reasoning for dynamic knowledge graphs
Rakshit Trivedi, Hanjun Dai, Yichen Wang, and Le Song. 2017 · 2017
Later among the works it cites.
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Character-aware neural language models
Yoon Kim, Yacine Jernite, David Sontag, and Alexander M Rush. 2016 · 2016
Cited alongside, same era.
A review of relational machine learning for knowledge graphs
Maximilian Nickel, Kevin Murphy, Volker Tresp, and Evgeniy Gabrilovich. 2016 · 2016
Cited alongside, same era.
Deriving validity time in knowledge graph
Julien Leblay and Melisachew Wudage Chekol. 2018 · 2018
Closest in time.