| Adaptive deep learning for high-dimensional Hamilton--Jacobi--Bellman equations T Nakamura-Zimmerer, Q Gong, W Kang SIAM Journal on Scientific Computing 43 (2), A1221-A1247, 2021 | 150 | 2021 |
| QRnet: Optimal regulator design with LQR-augmented neural networks T Nakamura-Zimmerer, Q Gong, W Kang IEEE Control Systems Letters 5 (4), 1303-1308, 2020 | 47 | 2020 |
| Algorithms of data generation for deep learning and feedback design: A survey W Kang, Q Gong, T Nakamura-Zimmerer, F Fahroo Physica D: Nonlinear Phenomena 425, 132955, 2021 | 33 | 2021 |
| A causality-free neural network method for high-dimensional Hamilton-Jacobi-Bellman equations T Nakamura-Zimmerer, Q Gong, W Kang 2020 American Control Conference (ACC), 787-793, 2020 | 22 | 2020 |
| Neural Network Optimal Feedback Control with Guaranteed Local Stability T Nakamura-Zimmerer, Q Gong, W Kang IEEE Open Journal of Control Systems 1, 210-222, 2022 | 19* | 2022 |
| Neural network optimal feedback control with enhanced closed loop stability T Nakamura-Zimmerer, Q Gong, W Kang 2022 American Control Conference (ACC), 2373-2378, 2022 | 12 | 2022 |
| Multihierarchy Gaussian process models for probabilistic aerodynamic databases using uncertain nominal and off-nominal configuration data JB Scoggins, TJ Wignall, T Nakamura-Zimmerer, KL Bibb AIAA SCITECH 2023 Forum, 1185, 2023 | 7 | 2023 |
| Comparisons of performance metrics and machine learning methods on an entry descent and landing database TJ Wignall, T Nakamura-Zimmerer, JB Scoggins, S Snyder, S Kumar, ... AIAA SCITECH 2023 Forum, 1183, 2023 | 7 | 2023 |
| AeroFusion: Data Fusion and Uncertainty Quantification for Entry Vehicles S Snyder, TJ Wignall, JS Green, S Kumar, MW Lee, ... AIAA SCITECH 2023 Forum, 1182, 2023 | 6 | 2023 |
| Structured Covariance Gaussian Networks for Orion Crew Module Aerodynamic Uncertainty Quantification T Nakamura-Zimmerer, MT Stringer, BK Colbert, JB Scoggins AIAA SCITECH 2023 Forum, 1184, 2023 | 5 | 2023 |
| A deep learning framework for optimal feedback control of high-dimensional nonlinear systems TE Nakamura-Zimmerer University of California, Santa Cruz, 2022 | 4 | 2022 |
| Density propagation with characteristics-based deep learning T Nakamura-Zimmerer, D Venturi, Q Gong, W Kang arXiv preprint arXiv:1911.09311, 2019 | 1 | 2019 |
| An Actor Critic Machine Learning Method for Free Terminal Time Optimal Control E BURTON, T NAKAMURA-ZIMMERER, Q GONG, W KANG Journal of Systems Science and Complexity 38 (2), 1-21, 2025 | | 2025 |
| Trajectory Planning and Online Performance Model Estimation for Advanced Air Mobility T Nakamura-Zimmerer, A Patterson, MJ Acheson, IM Gregory AIAA SCITECH 2025 Forum, 1120, 2025 | | 2025 |
| An Actor Critic Method for Free Terminal Time Optimal Control E Burton, T Nakamura-Zimmerer, Q Gong, W Kang IFAC-PapersOnLine 56 (1), 49-54, 2023 | | 2023 |
Qi GongUniversity of California, Santa Cruzsoe.ucsc.edu üzerinde doğrulanmış e-posta adresine sahip
