| Controlling Rayleigh–Bénard convection via reinforcement learning G Beintema, A Corbetta, L Biferale, F Toschi Journal of Turbulence 21 (9-10), 585-605, 2020 | 67 | 2020 |
| Nonlinear state-space identification using deep encoder networks G Beintema, R Toth, M Schoukens Learning for dynamics and control, 241-250, 2021 | 29 | 2021 |
| Non-linear state-space model identification from video data using deep encoders GI Beintema, R Toth, M Schoukens IFAC-PapersOnLine 54 (7), 697-701, 2021 | 11 | 2021 |
| Deep identification of nonlinear systems in Koopman form LC Iacob, GI Beintema, M Schoukens, R Tóth 2021 60th IEEE Conference on Decision and Control (CDC), 2288-2293, 2021 | 10 | 2021 |
| Identification of the nonlinear steering dynamics of an autonomous vehicle G Rödönyi, GI Beintema, R Tóth, M Schoukens, D Pup, Á Kisari, Z Vígh, ... IFAC-PapersOnLine 54 (7), 708-713, 2021 | 5 | 2021 |
| Deep subspace encoders for nonlinear system identification GI Beintema, M Schoukens, R Tóth Automatica 156, 111210, 2023 | 4 | 2023 |
| Deep-learning-based identification of lpv models for nonlinear systems C Verhoek, GI Beintema, S Haesaert, M Schoukens, R Tóth 2022 IEEE 61st Conference on Decision and Control (CDC), 3274-3280, 2022 | 4 | 2022 |
| NARX identification using derivative-based regularized neural networks LH Peeters, GI Beintema, M Forgione, M Schoukens 2022 IEEE 61st Conference on Decision and Control (CDC), 1515-1520, 2022 | 1 | 2022 |
| Continuous-time identification of dynamic state-space models by deep subspace encoding GI Beintema, M Schoukens, R Tóth arXiv preprint arXiv:2204.09405, 2022 | 1 | 2022 |
| Reinforcement learning versus linear control of Rayleigh-Bénard convection A Corbetta, G Beintema, L Biferale, P Kumar, F Toschi APS Division of Fluid Dynamics Meeting Abstracts, P17. 006, 2019 | 1 | 2019 |
| Meta-State-Space Learning: An Identification Approach for Stochastic Dynamical Systems GI Beintema, M Schoukens, R Tóth arXiv preprint arXiv:2307.06675, 2023 | | 2023 |
| Identifying a simulation model of an industrial robot A Retzler, R Tóth, GI Beintema, JP Noël, M Schoukens, J Weigand, ... 7th Edition of the Workshop on Nonlinear System Identification Benchmarks …, 2023 | | 2023 |
| Output error port Hamiltonian neural networks: a Silverbox example S Moradi, GI Beintema, NO Jaensson, R Tóth, M Schoukens 2023 Workshop on Nonlinear System Identification Benchmarks, 2023 | | 2023 |
| Initialization Approach for Nonlinear State-Space Identification via the Subspace Encoder Approach R Ramkannan, GI Beintema, R Tóth, M Schoukens arXiv preprint arXiv:2304.02119, 2023 | | 2023 |
| Computationally efficient predictive control based on ANN state-space model JH Hoekstra, B Cseppentő, GI Beintema, M Schoukens, Z Kollár, R Tóth arXiv preprint arXiv:2303.17305, 2023 | | 2023 |
| Augmented model identification for forward simulation of a robot arm A Retzler, R Tóth, J Swevers, JP Noël, Z Kollár, GI Beintema, J Weigand, ... Benelux Meeting on Systems and Control 2023, Location: Elspeet, The Netherlands, 2023 | | 2023 |
| Learning-Based Model-Augmentation of Nonlinear Approximative Models using the Sub-Space Encoder C Verhoek, GI Beintema, S Haesaert, M Schoukens, R Tóth 41st Benelux Meeting on Systems and Control 2022, 52-52, 2022 | | 2022 |
| Learning-based augmentation of mechatronic system models by deep subspace encoders A Retzler, G Beintema, M Schoukens, T Roland, J Swevers, Z Kollár Benelux Meeting on Systems and Control 2022, Location: Brussels, Belgium, 2022 | | 2022 |
| Continuous-time identification of dynamic state-space models by deep subspace encoding GI Beintema, M Schoukens, R Tóth arXiv preprint arXiv:2204.09405, 2022 | | 2022 |
| Deep Learning-based Identification of Koopman Models with Inputs LC Iacob, GI Beintema, M Schoukens, R Tóth | | 2022 |
Roland TothAssociate Professor, Eindhoven University of TechnologyBestätigte E-Mail-Adresse bei tue.nl
