Sicun Gao
Sicun Gao
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Zitiert von
Zitiert von
dReal: An SMT solver for nonlinear theories over the reals
S Gao, S Kong, EM Clarke
International conference on automated deduction, 208-214, 2013
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
Neural lyapunov control
YC Chang, N Roohi, S Gao
Advances in neural information processing systems 32, 2019
δ-Complete Decision Procedures for Satisfiability over the Reals
S Gao, J Avigad, EM Clarke
International Joint Conference on Automated Reasoning, 286-300, 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, 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
Satisfiability modulo odes
S Gao, S Kong, EM Clarke
2013 Formal Methods in Computer-Aided Design, 105-112, 2013
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
Delta-decidability over the reals
S Gao, J Avigad, EM Clarke
2012 27th Annual IEEE Symposium on Logic in Computer Science, 305-314, 2012
SMT-based nonlinear PDDL+ planning
D Bryce, S Gao, D Musliner, R Goldman
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
Counting zeros over finite fields with Gröbner bases
S Gao
Master’s thesis, Carnegie Mellon University, 2009
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
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
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
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
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
APEX: Autonomous vehicle plan verification and execution
ME O'Kelly, H Abbas, S Gao, S Kato, S Shiraishi, R Mangharam
SAE Technical Paper, 2016
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
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
Delta-complete analysis for bounded reachability of hybrid systems
S Gao, S Kong, W Chen, E Clarke
arXiv preprint arXiv:1404.7171, 2014
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