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A major challenge in applying machine learning to automated theorem proving is the scarcity of training data, which is a key ingredient in training successful deep learning models.
The logic theory machine–a complex information processing system
Allen Newell and Herbert Simon · 1956
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J. A. Robinson · 1965
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A completeness theorem and computer program for finding theorems derivable from given axioms
Char-Tung Lee · 1967
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A note on inductive generalization
G. D. Plotkin · 1970
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Automated theory formation in mathematics
Douglas B Lenat · 1977
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Reiner Hähnle · 2001
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Koen Claessen, Reiner Hähnle, and Johan Mårtensson · 2002
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Alexandre Riazanov and Andrei Voronkov · 2002
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Approximate reasoning in first-order logic theories
Johan Wittocx, Maarten Mariën, and Marc Denecker · 2008
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Rectified linear units improve restricted boltzmann machines
Vinod Nair and Geoffrey E Hinton · 2010
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Melvin Fitting · 2012
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Cezary Kaliszyk, Josef Urban, Henryk Michalewski, and Miroslav Olšák · 2018
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A deep reinforcement learning based approach to learning transferable proof guidance strategies
Maxwell Crouse, Spencer Whitehead, Ibrahim Abdelaziz, Bassem Makni, Cristina Cornelio, Pavan Kapanipathi, Edwin Pell, Kavitha Srinivas, Veronika Thost, Michael Witbrock, and Achille Fokoue · 2019
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