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DeepProbLog :
DeepProbLog : Neural Probabilistic Logic Programming
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- Manhaeve, Robin (author)
- Katholieke Universiteit Leuven, Leuven, Belgium
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- Dumancic, Sebastijan (author)
- Katholieke Universiteit Leuven, Leuven, Belgium
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- Kimmig, Angelika (author)
- Cardiff University, Cardiff, England
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- Demeester, Thomas (author)
- Ghent University, Ghent, Belgium
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- De Raedt, Luc, 1964- (author)
- Katholieke Universiteit Leuven, Leuven, Belgium
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(creator_code:org_t)
- Neural Information Processing Systems Foundation Inc. 2018
- 2018
- English.
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In: Advances in Neural Information Processing Systems 31 (NIPS 2018). - : Neural Information Processing Systems Foundation Inc.. ; , s. 3753-3760
- Related links:
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https://urn.kb.se/re...
Abstract
Subject headings
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- We introduce DeepProbLog, a probabilistic logic programming language that in-corporates deep learning by means of neural predicates. We show how existing inference and learning techniques can be adapted for the new language. Our experiments demonstrate that DeepProbLog supports (i) both symbolic and sub-symbolic representations and inference, (ii) program induction, (iii) probabilistic(logic) programming, and (iv) (deep) learning from examples. To the best of our knowledge, this work is the first to propose a framework where general-purpose neural networks and expressive probabilistic-logical modeling and reasoning are integrated in a way that exploits the full expressiveness and strengths of both worlds and can be trained end-to-end based on examples.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Publication and Content Type
- ref (subject category)
- kon (subject category)
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