| dReal: An SMT Solver for Nonlinear Theories over the Reals S Gao, S Kong, EM Clarke International conference on automated deduction, 208-214, 2013 | 428 | 2013 |
| dReach: δ-Reachability Analysis for Hybrid Systems S Kong, S Gao, W Chen, E Clarke International Conference on TOOLS and Algorithms for the Construction and …, 2015 | 283 | 2015 |
| δ-complete decision procedures for satisfiability over the reals S Gao, J Avigad, EM Clarke International Joint Conference on Automated Reasoning, 286-300, 2012 | 181 | 2012 |
| Neural lyapunov control YC Chang, N Roohi, S Gao Advances in neural information processing systems 32, 2019 | 126 | 2019 |
| Satisfiability modulo odes S Gao, S Kong, EM Clarke 2013 Formal Methods in Computer-Aided Design, 105-112, 2013 | 109 | 2013 |
| A non-prenex, non-clausal QBF solver with game-state learning W Klieber, S Sapra, S Gao, E Clarke International Conference on Theory and Applications of Satisfiability …, 2010 | 93 | 2010 |
| SMT-based nonlinear PDDL+ planning D Bryce, S Gao, D Musliner, R Goldman Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015 | 88 | 2015 |
| Delta-decidability over the reals S Gao, J Avigad, EM Clarke 2012 27th Annual IEEE Symposium on Logic in Computer Science, 305-314, 2012 | 86 | 2012 |
| Integrating ICP and LRA solvers for deciding nonlinear real arithmetic problems S Gao, M Ganai, F Ivančić, A Gupta, S Sankaranarayanan, EM Clarke Formal Methods in Computer Aided Design, 81-89, 2010 | 55 | 2010 |
| Counting zeros over finite fields with Gröbner bases S Gao Master’s thesis, Carnegie Mellon University, 2009 | 53* | 2009 |
| APEX: Autonomous vehicle plan verification and execution M O'Kelly, H Abbas, S Gao, S Shiraishi, S Kato, R Mangharam | 32 | 2016 |
| Sreach: A probabilistic bounded delta-reachability analyzer for stochastic hybrid systems Q Wang, P Zuliani, S Kong, S Gao, EM Clarke International Conference on Computational Methods in Systems Biology, 15-27, 2015 | 27* | 2015 |
| Delta-complete analysis for bounded reachability of hybrid systems S Gao, S Kong, W Chen, E Clarke arXiv preprint arXiv:1404.7171, 2014 | 24 | 2014 |
| Releq: an automatic reinforcement learning approach for deep quantization of neural networks A Elthakeb, P Pilligundla, FS Mireshghallah, A Yazdanbakhsh, S Gao, ... NeurIPS ML for Systems workshop, 2018, 2019 | 23 | 2019 |
| Parameter synthesis for cardiac cell hybrid models using δ-decisions B Liu, S Kong, S Gao, P Zuliani, EM Clarke International Conference on Computational Methods in Systems Biology, 99-113, 2014 | 21* | 2014 |
| Automated vulnerability analysis of AC state estimation under constrained false data injection in electric power systems S Gao, L Xie, A Solar-Lezama, D Serpanos, H Shrobe 2015 54th ieee conference on decision and control (cdc), 2613-2620, 2015 | 20 | 2015 |
| Quantifier elimination over finite fields using Gröbner bases S Gao, A Platzer, EM Clarke International Conference on Algebraic Informatics, 140-157, 2011 | 19 | 2011 |
| How to pick the domain randomization parameters for sim-to-real transfer of reinforcement learning policies? Q Vuong, S Vikram, H Su, S Gao, HI Christensen arXiv preprint arXiv:1903.11774, 2019 | 17 | 2019 |
| Towards personalized prostate cancer therapy using delta-reachability analysis B Liu, S Kong, S Gao, P Zuliani, EM Clarke Proceedings of the 18th International Conference on Hybrid Systems …, 2015 | 17 | 2015 |
| Computable analysis, decision procedures, and hybrid automata: a new framework for the formal verification of cyber-physical systems S Gao PhD thesis, Carnegie Mellon University, 2012 | 16* | 2012 |
