Enhancing opacity of stochastic discrete event systems using insertion functions. - Yi-Chin Wu; Gil Lederman; Stéphane Lafortune (ACC, 2016)

Learning Heuristics for Automated Reasoning through Deep Reinforcement Learning. - Gil Lederman; Markus N. Rabe; Sanjit A. Seshia (CoRR, 2018)

Learning Heuristics for Quantified Boolean Formulas through Reinforcement Learning. - Gil Lederman; Markus N. Rabe; Sanjit Seshia; Edward A. Lee (ICLR, 2020)

Learning Branching Heuristics for Propositional Model Counting. - Pashootan Vaezipoor; Gil Lederman; Yuhuai Wu; Chris J. Maddison; Roger B. Grosse; Edward A. Lee; Sanjit A. Seshia; Fahiem Bacchus (CoRR, 2020)

Gordian: Formal Reasoning-based Outlier Detection for Secure Localization. - Matthew Weber; Baihong Jin; Gil Lederman; Yasser Shoukry; Edward A. Lee; Sanjit Seshia; Alberto L. Sangiovanni-Vincentelli (ACM Trans. Cyber Phys. Syst., 2020)

Learning Branching Heuristics for Propositional Model Counting. - Pashootan Vaezipoor; Gil Lederman; Yuhuai Wu; Chris J. Maddison; Roger B. Grosse; Sanjit A. Seshia; Fahiem Bacchus (AAAI, 2021)

Demonstration Informed Specification Search. - Marcell Vazquez-Chanlatte; Ameesh Shah; Gil Lederman; Sanjit A. Seshia (CoRR, 2021)

Neural Guidance in Constraint Solvers. - Gil Lederman (2021)

Rotation Invariant Quantization for Model Compression. - Joseph Kampeas; Yury Nahshan; Hanoch Kremer; Gil Lederman; Shira Zaloshinski; Zheng Li; Emir Haleva (CoRR, 2023)

Does the Performance of Text-to-Image Retrieval Models Generalize Beyond Captions-as-a-Query? - Juan Manuel Rodriguez; Nima Tavassoli; Eliezer Levy; Gil Lederman; Dima Sivov; Matteo Lissandrini; Davide Mottin (ECIR (4), 2024)