| dReal: An SMT solver for nonlinear theories over the reals S Gao, S Kong, EM Clarke International conference on automated deduction, 208-214, 2013 | 577 | 2013 |
| Neural lyapunov control YC Chang, N Roohi, S Gao Advances in neural information processing systems 32, 2019 | 365 | 2019 |
| dReach: δ-Reachability Analysis for Hybrid Systems S Kong, S Gao, W Chen, E Clarke Tools and Algorithms for the Construction and Analysis of Systems: 21st …, 2015 | 354 | 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 | 237 | 2012 |
| Safe control with learned certificates: A survey of neural lyapunov, barrier, and contraction methods for robotics and control C Dawson, S Gao, C Fan IEEE Transactions on Robotics 39 (3), 1749-1767, 2023 | 216* | 2023 |
| Safe nonlinear control using robust neural lyapunov-barrier functions C Dawson, Z Qin, S Gao, C Fan Conference on Robot Learning, 1724-1735, 2022 | 167 | 2022 |
| Satisfiability modulo odes S Gao, S Kong, EM Clarke 2013 Formal Methods in Computer-Aided Design, 105-112, 2013 | 114 | 2013 |
| Delta-decidability over the reals S Gao, J Avigad, EM Clarke 2012 27th Annual IEEE Symposium on Logic in Computer Science, 305-314, 2012 | 98 | 2012 |
| A non-prenex, non-clausal QBF solver with game-state learning W Klieber, S Sapra, S Gao, E Clarke Theory and Applications of Satisfiability Testing–SAT 2010: 13th …, 2010 | 98 | 2010 |
| SMT-based nonlinear PDDL+ planning D Bryce, S Gao, D Musliner, R Goldman Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 94 | 2015 |
| Counting zeros over finite fields with Gröbner bases S Gao Master’s thesis, Carnegie Mellon University, 2009 | 60* | 2009 |
| Stabilizing neural control using self-learned almost lyapunov critics YC Chang, S Gao 2021 IEEE International Conference on Robotics and Automation (ICRA), 1803-1809, 2021 | 58 | 2021 |
| 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 | 57 | 2010 |
| Reducing collision checking for sampling-based motion planning using graph neural networks C Yu, S Gao Advances in Neural Information Processing Systems 34, 4274-4289, 2021 | 55 | 2021 |
| A neural Lyapunov approach to transient stability assessment of power electronics-interfaced networked microgrids T Huang, S Gao, L Xie IEEE transactions on smart grid 13 (1), 106-118, 2021 | 55 | 2021 |
| 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 | 49 | 2019 |
| Participatory algorithmic management: Elicitation methods for worker well-being models MK Lee, I Nigam, A Zhang, J Afriyie, Z Qin, S Gao Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 715-726, 2021 | 38 | 2021 |
| APEX: Autonomous vehicle plan verification and execution ME O'Kelly, H Abbas, S Gao, S Kato, S Shiraishi, R Mangharam SAE Technical Paper, 2016 | 38 | 2016 |
| 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 | 37 | 2019 |
| VeriSketch: Synthesizing secure hardware designs with timing-sensitive information flow properties A Ardeshiricham, Y Takashima, S Gao, R Kastner Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications …, 2019 | 33 | 2019 |
