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Gerben Beintema
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Year
Controlling Rayleigh–Bénard convection via reinforcement learning
G Beintema, A Corbetta, L Biferale, F Toschi
Journal of Turbulence 21 (9-10), 585-605, 2020
922020
Nonlinear state-space identification using deep encoder networks
G Beintema, R Toth, M Schoukens
Learning for dynamics and control, 241-250, 2021
432021
Deep subspace encoders for nonlinear system identification
GI Beintema, M Schoukens, R Tóth
Automatica 156, 111210, 2023
242023
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
172021
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
152021
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
112022
Continuous-time identification of dynamic state-space models by deep subspace encoding
GI Beintema, M Schoukens, R Tóth
arXiv preprint arXiv:2204.09405, 2022
92022
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
82021
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
32022
Computationally efficient predictive control based on ANN state-space models
JH Hoekstra, B Cseppento, GI Beintema, M Schoukens, Z Kollár, R Tóth
2023 62nd IEEE Conference on Decision and Control (CDC), 6336-6341, 2023
22023
Meta-state–space learning: An identification approach for stochastic dynamical systems
GI Beintema, M Schoukens, R Tóth
Automatica 167, 111787, 2024
12024
Data–driven Learning of Nonlinear Dynamic Systems: A Deep Neural State–Space Approach
GI Beintema
12024
State Derivative Normalization for Continuous-Time Deep Neural Networks
J Weigand, GI Beintema, J Ulmen, D Görges, R Tóth, M Schoukens, ...
arXiv preprint arXiv:2401.02902, 2024
12024
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
12022
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
12019
Baseline Results for Selected Nonlinear System Identification Benchmarks
MD Champneys, GI Beintema, R Tóth, M Schoukens, TJ Rogers
arXiv preprint arXiv:2405.10779, 2024
2024
Output error port-Hamiltonian neural networks: Cascaded tanks system with overflow
S Moradi, GI Beintema, NO Jaensson, R Tóth, M Schoukens
Workshop on Nonlinear System Identification Benchmarks, 2024
2024
Meta-state-space Identification of Stochastic Hearts
GI Beintema, TB Schön, R Tóth, M Schoukens
43rd Benelux Meeting on Systems and Control, 2024
2024
Learning-based augmentation of physics-based models: an industrial robot use case
A Retzler, R Tóth, M Schoukens, GI Beintema, J Weigand, JP Noël, ...
Data-Centric Engineering 5, e12, 2024
2024
Output Error Port-Hamiltonian Neural Network
S Moradi, GI Beintema, NO Jaensson, R Tóth, M Schoukens
31st Workshop of the European Research Network on System Identification, 2023
2023
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Articles 1–20