Learning Continuous Semantic Representations of Symbolic Expressions

ICML 2017 Miltiadis AllamanisPankajan ChanthirasegaranPushmeet KohliCharles Sutton

Combining abstract, symbolic reasoning with continuous neural reasoning is a grand challenge of representation learning. As a step in this direction, we propose a new architecture, called neural equivalence networks, for the problem of learning continuous semantic representations of algebraic and logical expressions... (read more)

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