[1606.04442] DeepMath

DeepMath: deep learning + theorem proving  #math #MachineLearning

  • Abstract: We study the effectiveness of neural sequence models for premise selection in automated theorem proving, one of the main bottlenecks in the formalization of mathematics.
  • We propose a two stage approach for this task that yields good results for the premise selection task on the Mizar corpus while avoiding the hand-engineered features of existing state-of-the-art models.
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@algoritmic: “DeepMath: deep learning + theorem proving #math #MachineLearning”


One hundred percent of your contribution will fund improvements and new initiatives to benefit arXiv’s global scientific community. Please join the Simons Foundation and our generous member organizations and research labs in supporting arXiv.


[1606.04442] DeepMath