| Reinforcement Learning for Optimal Feedback Control: A Lyapunov-Based Approach R Kamalapurkar, P Walters, J Rosenfeld, W Dixon Springer, 2018 | 176* | 2018 |
| Verification for Machine Learning, Autonomy, and Neural Networks Survey W Xiang, P Musau, AA Wild, DM Lopez, N Hamilton, X Yang, J Rosenfeld, ... arXiv preprint arXiv:1810.01989, 2018 | 123 | 2018 |
| Efficient model-based reinforcement learning for approximate online optimal control R Kamalapurkar, JA Rosenfeld, WE Dixon Automatica 74, 247-258, 2016 | 104 | 2016 |
| Reachable set estimation and safety verification for piecewise linear systems with neural network controllers W Xiang, HD Tran, JA Rosenfeld, TT Johnson 2018 Annual American Control Conference (ACC), 1574-1579, 2018 | 81 | 2018 |
| Invariance-Like Results for Nonautonomous Switched Systems R Kamalapurkar, JA Rosenfeld, A Parikh, AR Teel, WE Dixon IEEE Transactions on Automatic Control 64 (2), 614-627, 2019 | 62 | 2019 |
| Supporting lemmas for RISE-based control methods R Kamalapurkar, JA Rosenfeld, J Klotz, RJ Downey, WE Dixon arXiv preprint arXiv:1306.3432, 2013 | 53 | 2013 |
| Decentralized formation control with connectivity maintenance and collision avoidance under limited and intermittent sensing TH Cheng, Z Kan, JA Rosenfeld, WE Dixon 2014 American control conference, 3201-3206, 2014 | 45 | 2014 |
| Dynamic mode decomposition for continuous time systems with the Liouville operator JA Rosenfeld, R Kamalapurkar, LF Gruss, TT Johnson Journal of Nonlinear Science 32, 1-30, 2022 | 41 | 2022 |
| Approximate Optimal Motion Planning to Avoid Unknown Moving Avoidance Regions P Deptula, HY Chen, RA Licitra, JA Rosenfeld, WE Dixon IEEE Transactions on Robotics 36 (2), 414-430, 2019 | 41 | 2019 |
| Approximate Dynamic Programming: Combining Regional and Local State Following Approximations P Deptula, JA Rosenfeld, R Kamalapurkar, WE Dixon IEEE transactions on neural networks and learning systems 29 (6), 2154-2166, 2018 | 33 | 2018 |
| The Occupation Kernel Method for Nonlinear System Identification JA Rosenfeld, B Russo, R Kamalapurkar, TT Johnson arXiv preprint arXiv:1909.11792, 2019 | 31 | 2019 |
| Occupation Kernels and Densely Defined Liouville Operators for System Identification JA Rosenfeld, R Kamalapurkar, B Russo, TT Johnson 2019 IEEE 58th Conference on Decision and Control (CDC), 6455-6460, 2019 | 29 | 2019 |
| Approximating the Caputo Fractional Derivative through the Mittag-Leffler Reproducing Kernel Hilbert Space and the Kernelized Adams--Bashforth--Moulton Method JA Rosenfeld, WE Dixon SIAM Journal on Numerical Analysis 55 (3), 1201-1217, 2017 | 29 | 2017 |
| The Mittag Leffler reproducing kernel Hilbert spaces of entire and analytic functions JA Rosenfeld, B Russo, WE Dixon Journal of Mathematical Analysis and Applications 463 (2), 576-592, 2018 | 24 | 2018 |
| A mesh-free pseudospectral approach to estimating the fractional Laplacian via radial basis functions JA Rosenfeld, SA Rosenfeld, WE Dixon Journal of Computational Physics 390, 306-322, 2019 | 23 | 2019 |
| The State Following Approximation Method JA Rosenfeld, R Kamalapurkar, WE Dixon IEEE transactions on neural networks and learning systems 30 (6), 1716-1730, 2018 | 20 | 2018 |
| Dynamic Mode Decomposition with Control Liouville Operators JA Rosenfeld, R Kamalapurkar IEEE Transactions on Automatic Control, 2024 | 18 | 2024 |
| The gradient descent method from the perspective of fractional calculus PV Hai, JA Rosenfeld Mathematical Methods in the Applied Sciences 44 (7), 5520-5547, 2021 | 15 | 2021 |
| The kernel perspective on dynamic mode decomposition E Gonzalez, M Abudia, M Jury, R Kamalapurkar, JA Rosenfeld arXiv preprint arXiv:2106.00106, 2021 | 14 | 2021 |
| State following (StaF) kernel functions for function approximation Part II: Adaptive dynamic programming R Kamalapurkar, JA Rosenfeld, WE Dixon 2015 American Control Conference (ACC), 521-526, 2015 | 14 | 2015 |
Rushikesh KamalapurkarUniversity of FloridaGeverifieerd e-mailadres voor ufl.edu