52 citations · 63 across the 4 of their papers we have counts for
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cs.LG2019★ 52 cited
An Inductive Synthesis Framework for Verifiable Reinforcement Learning
He Zhu, Zikang Xiong, Stephen Magill +1
Despite the tremendous advances that have been made in the last decade on developing useful machine-learning applications, their wider adoption has been hindered by the lack of str…
cs.LG2019★ 6 cited
ART: Abstraction Refinement-Guided Training for Provably Correct Neural Networks
Xuankang Lin, He Zhu, Roopsha Samanta +1
Artificial Neural Networks (ANNs) have demonstrated remarkable utility in various challenging machine learning applications. While formally verified properties of their behaviors a…