DeepMath - Deep Sequence Models for Premise Selection

Code

• github.com/BartoszPiotrowski/ATPboost
  none★ 0
• github.com/JUrban/deepmath
  none★ 0

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. To our knowledge, this is the first time deep learning has been applied to theorem proving on a large scale.

Tasks

Reproductions