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Large knowledge bases (KBs) are useful in many tasks, but it is unclear how to integrate this sort of knowledge into "deep" gradient-based learning systems.
Refinement of approximate domain theories by knowledge-based artificial neural networks
Geoffrey Towell, Jude Shavlik, and Michiel Noordewier · 1990
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The independent choice logic for modelling multiple agents under uncertainty
David Poole · 1997
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Parameter estimation in stochastic logic programs
James Cussens · 2001
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Markov logic networks
Matthew Richardson and Pedro Domingos · 2006
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Probabilistic inductive logic programming
Luc De Raedt and Kristian Kersting · 2008
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Probabilistic similarity logic
Matthias Brocheler, Lilyana Mihalkova, and Lise Getoor · 2010
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Semi-supervised classification of network data using very few labels
Frank Lin and William W. Cohen · 2010
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Probabilistic databases
Dan Suciu, Dan Olteanu, Christopher Ré, and Christoph Koch · 2011
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Programming with personalized PageRank: a locally groundable first-order probabilistic logic
William Yang Wang, Kathryn Mazaitis, and William W Cohen · 2013
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Structure learning via parameter learning
William Yang Wang, Kathryn Mazaitis, and William W Cohen · 2014
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Approximation-aware dependency parsing by belief propagation
Matthew R. Gormley, Mark Dredze, and Jason Eisner · 2015
Cited alongside, same era.
Lifted graphical models: a survey
Angelika Kimmig, Lilyana Mihalkova, and Lise Getoor · 2015
Cited alongside, same era.
Injecting logical background knowledge into embeddings for relation extraction
Tim Rocktäschel, Sameer Singh, and Sebastian Riedel · 2015
Later among the works it cites.
Lifted relational neural networks
Gustav Sourek, Vojtech Aschenbrenner, Filip Zelezný, and Ondrej Kuzelka · 2015
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Learning to compose neural networks for question answering
Jacob Andreas, Marcus Rohrbach, Trevor Darrell, and Dan Klein · 2016
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Inference and learning in probabilistic logic programs using weighted boolean formulas
Daan Fierens, Guy Van Den Broeck, Joris Renkens, Dimitar Shterionov, Bernd Gutmann, Ingo Thon, Gerda Janssens, and Luc De Raedt · 2016
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Learning knowledge base inference with neural theorem provers
Tim Rocktäschel and Sebastian Riedel · 2016
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Learning first-order logic embeddings via matrix factorization
William Yang Wang and William W. Cohen · 2016
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