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Schoukens, Maarten
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1

Measurements and System Identification for the Characteriza..:

, In: 2024 IEEE International Symposium on Medical Measurements and Applications (MeMeA),
Ozturk, Dilan ; Saraber, Pepijn ; Bielawski, Kevin... - p. 1-6 , 2024
Link: https://doi.org/10.1109/..
 
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2

Learning-based augmentation of physics-based models: an ind..:

Retzler, András ; Tóth, Roland ; Schoukens, Maarten...
Data-Centric Engineering.  5 (2024)  - p. , 2024
Link: https://doi.org/10.1017/..
 
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3

Meta-state–space learning: An identification approach for s..:

Beintema, Gerben I. ; Schoukens, Maarten ; Tóth, Roland
Automatica.  167 (2024)  - p. 111787 , 2024
Link: https://doi.org/10.1016/..
 
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4

Identification of structured nonlinear state–space models f..:

Krikelis, Konstantinos ; Pei, Jin-Song ; van Berkel, Koos.
Measurement.  224 (2024)  - p. 113966 , 2024
Link: https://doi.org/10.1016/..
 
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5

Koopman form of nonlinear systems with inputs:

Iacob, Lucian Cristian ; Tóth, Roland ; Schoukens, Maarten
Automatica.  162 (2024)  - p. 111525 , 2024
Link: https://doi.org/10.1016/..
 
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6

Deep subspace encoders for nonlinear system identification:

Beintema, Gerben I. ; Schoukens, Maarten ; Tóth, Roland
Automatica.  156 (2023)  - p. 111210 , 2023
Link: https://doi.org/10.1016/..
 
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7

Computationally Efficient Predictive Control Based on ANN S..:

, In: 2023 62nd IEEE Conference on Decision and Control (CDC),
Hoekstra, Jan H. ; Cseppento, Bence ; Beintema, Gerben I.... - p. 6336-6341 , 2023
Link: https://doi.org/10.1109/..
 
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8

Nonlinear Data-Driven Predictive Control Using Deep Subspac..:

, In: 2023 62nd IEEE Conference on Decision and Control (CDC),
Lazar, Mircea ; Popescu, Mihai-Serban ; Schoukens, Maarten - p. 3770-3775 , 2023
Link: https://doi.org/10.1109/..
 
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9

Automated multi-objective system identification using gramm..:

Khandelwal, Dhruv ; Schoukens, Maarten ; Tóth, Roland
Automatica.  154 (2023)  - p. 111017 , 2023
Link: https://doi.org/10.1016/..
 
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10

Deep-Learning-Based Identification of LPV Models for Nonlin..:

, In: 2022 IEEE 61st Conference on Decision and Control (CDC),
Verhoek, Chris ; Beintema, Gerben I. ; Haesaert, Sofie.. - p. 3274-3280 , 2022
Link: https://doi.org/10.1109/..
 
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11

Variational message passing for online polynomial NARMAX id..:

, In: 2022 American Control Conference (ACC),
Kouw, WouterM. ; Podusenko, Albert ; Koudahl, MagnusT.. - p. 2755-2760 , 2022
Link: https://doi.org/10.23919..
 
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12

Message Passing-based System Identification for NARMAX Mode..:

, In: 2022 IEEE 61st Conference on Decision and Control (CDC),
Podusenko, Albert ; Akbayrak, Semih ; Senoz, Ismail.. - p. 7309-7314 , 2022
Link: https://doi.org/10.1109/..
 
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13

Feedback identification of conductance-based models:

Burghi, Thiago B. ; Schoukens, Maarten ; Sepulchre, Rodolphe
Automatica.  123 (2021)  - p. 109297 , 2021
Link: https://doi.org/10.1016/..
 
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14

Data-driven Modeling of Impedance Biosensors: A Subspace Ap..:

Ramírez-Chavarría, Roberto Giovanni ; Alvarez-Serna, Bryan Emmanuel ; Schoukens, Maarten.
Measurement Science and Technology.  , 2021
Link: https://doi.org/10.1088/..
 
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15

A Tree Adjoining Grammar representation for models of stoch..:

Khandelwal, Dhruv ; Schoukens, Maarten ; Tóth, Roland
Automatica.  119 (2020)  - p. 109099 , 2020
Link: https://doi.org/10.1016/..
 
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