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2020 – today
- 2024
[j2]Gerben Izaak Beintema
, Maarten Schoukens, Roland Tóth:
Meta-state-space learning: An identification approach for stochastic dynamical systems. Autom. 167: 111787 (2024)- [i14]Jonas Weigand, Gerben Izaak Beintema, Jonas Ulmen, Daniel Görges, Roland Tóth, Maarten Schoukens, Martin Ruskowski:
State Derivative Normalization for Continuous-Time Deep Neural Networks. CoRR abs/2401.02902 (2024) - [i13]Max D. Champneys, Gerben Izaak Beintema, Roland Tóth, Maarten Schoukens, Timothy J. Rogers:
Baseline Results for Selected Nonlinear System Identification Benchmarks. CoRR abs/2405.10779 (2024) - 2023
- [j1]Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth:
Deep subspace encoders for nonlinear system identification. Autom. 156: 111210 (2023) - [c6]Jan H. Hoekstra, Bence Cseppento, Gerben Izaak Beintema, Maarten Schoukens, Zsolt Kollár, Roland Tóth:
Computationally Efficient Predictive Control Based on ANN State-Space Models. CDC 2023: 6336-6341 - [c5]Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth:
Continuous-time identification of dynamic state-space models by deep subspace encoding. ICLR 2023 - [i12]Jan H. Hoekstra, Bence Cseppento, Gerben Izaak Beintema, Maarten Schoukens, Zsolt Kollár, Roland Tóth:
Computationally efficient predictive control based on ANN state-space models. CoRR abs/2303.17305 (2023) - [i11]Rishi Ramkannan, Gerben Izaak Beintema, Roland Tóth, Maarten Schoukens:
Initialization Approach for Nonlinear State-Space Identification via the Subspace Encoder Approach. CoRR abs/2304.02119 (2023) - [i10]Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth:
Meta-State-Space Learning: An Identification Approach for Stochastic Dynamical Systems. CoRR abs/2307.06675 (2023) - 2022
- [c4]L. H. Peeters, Gerben Izaak Beintema, M. Forgione, Maarten Schoukens:
NARX Identification using Derivative-Based Regularized Neural Networks. CDC 2022: 1515-1520 - [c3]Chris Verhoek, Gerben Izaak Beintema, Sofie Haesaert, Maarten Schoukens, Roland Tóth:
Deep-Learning-Based Identification of LPV Models for Nonlinear Systems. CDC 2022: 3274-3280 - [i9]Chris Verhoek, Gerben Izaak Beintema, Sofie Haesaert, Maarten Schoukens, Roland Tóth:
Deep-Learning-Based Identification of LPV Models for Nonlinear Systems. CoRR abs/2204.04060 (2022) - [i8]L. H. Peeters, Gerben Izaak Beintema, M. Forgione, Maarten Schoukens:
NARX Identification using Derivative-Based Regularized Neural Networks. CoRR abs/2204.05892 (2022) - [i7]Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth:
Deep subspace encoders for continuous-time state-space identification. CoRR abs/2204.09405 (2022) - [i6]Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth:
Deep Subspace Encoders for Nonlinear System Identification. CoRR abs/2210.14816 (2022) - 2021
- [c2]Lucian-Cristian Iacob, Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth:
Deep Identification of Nonlinear Systems in Koopman Form. CDC 2021: 2288-2293 - [c1]Gerben Beintema, Roland Tóth, Maarten Schoukens:
Nonlinear state-space identification using deep encoder networks. L4DC 2021: 241-250 - [i5]Gábor Rödönyi, Gerben Izaak Beintema, Roland Tóth, Maarten Schoukens, Daniel Pup, Ádám Kisari, Zs. Vígh, Péter Korös, Alexandros Soumelidis, József Bokor:
Identification of the nonlinear steering dynamics of an autonomous vehicle. CoRR abs/2105.04529 (2021) - [i4]Lucian-Cristian Iacob, Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth:
Deep Identification of Nonlinear Systems in Koopman Form. CoRR abs/2110.02583 (2021) - 2020
- [i3]Gerben Beintema, Alessandro Corbetta, Luca Biferale, Federico Toschi:
Controlling Rayleigh-Bénard convection via Reinforcement Learning. CoRR abs/2003.14358 (2020) - [i2]Gerben Beintema, Roland Tóth, Maarten Schoukens:
Nonlinear state-space identification using deep encoder networks. CoRR abs/2012.07697 (2020) - [i1]Gerben Izaak Beintema, Roland Tóth, Maarten Schoukens:
Non-linear State-space Model Identification from Video Data using Deep Encoders. CoRR abs/2012.07721 (2020)
Coauthor Index
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