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Property-Directed Verification of Recurrent Neural Networks


Sep 22, 2020
Igor Khmelnitsky, Daniel Neider, Rajarshi Roy, Benoît Barbot, Benedikt Bollig, Alain Finkel, Serge Haddad, Martin Leucker, Lina Ye


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Probably Approximately Correct Explanations of Machine Learning Models via Syntax-Guided Synthesis


Sep 18, 2020
Daniel Neider, Bishwamittra Ghosh


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Active Finite Reward Automaton Inference and Reinforcement Learning Using Queries and Counterexamples


Jun 28, 2020
Zhe Xu, Bo Wu, Daniel Neider, Ufuk Topcu


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A Formal Language Approach to Explaining RNNs


Jun 12, 2020
Bishwamittra Ghosh, Daniel Neider


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Learning Interpretable Models in the Property Specification Language


Feb 10, 2020
Rajarshi Roy, Dana Fisman, Daniel Neider


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Joint Inference of Reward Machines and Policies for Reinforcement Learning


Sep 12, 2019
Zhe Xu, Ivan Gavran, Yousef Ahmad, Rupak Majumdar, Daniel Neider, Ufuk Topcu, Bo Wu


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Learning-Based Synthesis of Safety Controllers


Jan 21, 2019
Daniel Neider, Oliver Markgraf


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Learning Linear Temporal Properties


Sep 20, 2018
Daniel Neider, Ivan Gavran


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Invariant Synthesis for Incomplete Verification Engines


Jan 12, 2018
Daniel Neider, Pranav Garg, P. Madhusudan, Shambwaditya Saha, Daejun Park


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Horn-ICE Learning for Synthesizing Invariants and Contracts


Dec 26, 2017
Deepak D'Souza, P. Ezudheen, Pranav Garg, P. Madhusudan, Daniel Neider


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An Automaton Learning Approach to Solving Safety Games over Infinite Graphs


Jan 07, 2016
Daniel Neider, Ufuk Topcu


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Learning Universally Quantified Invariants of Linear Data Structures


Feb 09, 2013
Pranav Garg, Christof Loding, P. Madhusudan, Daniel Neider


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