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Recovering missing CFD data for high-order discretizations using deep neural networks and dynamics learning.

, , , , , and . CoRR, (2018)

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Recovering missing CFD data for high-order discretizations using deep neural networks and dynamics learning., , , , , and . J. Comput. Phys., (2019)Dynamic Data Driven Application System for Plume Estimation Using UAVs., , and . Journal of Intelligent and Robotic Systems, 74 (1-2): 421-436 (2014)Symplectic Model Reduction of Hamiltonian Systems., and . SIAM J. Sci. Comput., (2016)A DDDAS Plume Monitoring System with Reduced Kalman Filter1., , and . ICCS, volume 51 of Procedia Computer Science, page 2533-2542. Elsevier, (2015)Cooperative control using data-driven feedback for mobile sensors., , , and . ICRA, page 772-777. IEEE, (2013)Recovering missing CFD data for high-order discretizations using deep neural networks and dynamics learning., , , , , and . CoRR, (2018)Non-intrusive nonlinear model reduction via machine learning approximations to low-dimensional operators., and . Adv. Model. Simul. Eng. Sci., 8 (1): 28 (2021)A localized symplectic model reduction technique for parameterized Hamiltonian systems., and . ACC, page 5545-5550. IEEE, (2015)An Online Manifold Learning Approach for Model Reduction of Dynamical Systems., and . SIAM J. Numerical Analysis, 52 (4): 1928-1952 (2014)High Resolution Atmospheric Sensing Using UAVs., , , and . DARS, volume 104 of Springer Tracts in Advanced Robotics, page 31-45. Springer, (2012)