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We present an implementation of a probabilistic first-order logic called TensorLog, in which classes of logical queries are compiled into differentiable functions in a neural-network infrastructure such as Tensorflow or Theano.
Refinement of approximate domain theories by knowledge-based artificial neural networks
Towell, G., Shavlik, J., & Noordewier, M. (1990) · 1990
Earlier work this paper cites.
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Ramakrishnan, R., & Ullman, J. D. (1995) · 1995
Earlier work this paper cites.
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Muggleton, S., et al. (1996) · 1996
Earlier work this paper cites.
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Poole, D. (1997) · 1997
Earlier work this paper cites.
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Cussens, J. (2001) · 2001
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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