Maarten Schoukens

111 papers A* 1B 1C 1Journal 82Unranked 26

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Encoder initialisation methods in the model augmentation setting. CoRR Jan H. Hoekstra, Bendegúz M. Györök, Roland Tóth, Maarten Schoukens
2026	J	`jnl`	Identification of Port-Hamiltonian Differential-Algebraic Equations from Input-Output Data. CoRR N. Hagelaars, G. J. E. van Otterdijk, Sarvin Moradi, Roland Tóth, Nick O. Jaensson, Maarten Schoukens
2026	J	`jnl`	Improved Initialization for Port-Hamiltonian Neural Network Models. CoRR G. J. E. van Otterdijk, Siep Weiland, Maarten Schoukens
2026	J	`jnl`	Learning-based augmentation of first-principle models: A linear fractional representation-based approach. CoRR Jan H. Hoekstra, Bendegúz M. Györök, Roland Tóth, Maarten Schoukens
2026	J	`jnl`	Orthogonal-by-construction augmentation of physics-based input-output models. IFAC J. Syst. Control. Bendegúz M. Györök, Maarten Schoukens, Tamás Péni, Roland Tóth
2026	J	`jnl`	Port-Hamiltonian neural networks with output error noise models. Autom. Sarvin Moradi, Gerben Izaak Beintema, Nick O. Jaensson, Roland Tóth, Maarten Schoukens
2025	—	`conf`	A frequency-domain approach for estimating continuous-time diffusively coupled linear networks. ECC Desen Liang, E. M. M. Lizan Kivits, Maarten Schoukens, Paul M. J. Van den Hof
2025	—	`conf`	Comparison of Black-Box Nonlinear System Identification Methods for Smooth Muscle Cell Dynamics ECC Dilan Öztürk, Maarten Schoukens
2025	—	`conf`	Designing positive excitation signals for the safe identification of nonlinear integrating systems. CDC Jan Jenneskens, Lennard Ceelen, Maarten Schoukens, Matthijs van Berkel
2025	J	`jnl`	Exact Finite Koopman Embedding of Block-Oriented Polynomial Systems. CoRR Lucian-Cristian Iacob, Roland Tóth, Maarten Schoukens
2025	J	`jnl`	Learning Koopman Models From Data Under General Noise Conditions. CoRR Lucian-Cristian Iacob, Máté Szécsi, Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth
2025	—	`conf`	Learning Subsystem Dynamics in Nonlinear Systems via Port-Hamiltonian Neural Networks. CDC G. J. E. van Otterdijk, Sarvin Moradi, Siep Weiland, Roland Tóth, Nick O. Jaensson, Maarten Schoukens
2025	J	`jnl`	Learning-based model augmentation with LFRs. Eur. J. Control Jan H. Hoekstra, Chris Verhoek, Roland Tóth, Maarten Schoukens
2025	J	`jnl`	On Space-Filling Input Design for Nonlinear Dynamic Model Learning: A Gaussian Process Approach. CoRR Yuhan Liu, Máté Kiss, Roland Tóth, Maarten Schoukens
2025	J	`jnl`	On Space-Filling Input Design for Nonlinear Dynamic Model Learning: A Gaussian Process Approach. IEEE Control. Syst. Lett. Yuhan Liu, Máté Kiss, Roland Tóth, Maarten Schoukens
2025	—	`conf`	Orthogonal projection-based regularization for efficient model augmentation. L4DC Bendegúz M. Györök, Jan H. Hoekstra, Johan Kon, Tamas Peni, Maarten Schoukens, Roland Tóth
2025	J	`jnl`	Orthogonal projection-based regularization for efficient model augmentation. CoRR Bendegúz M. Györök, Jan H. Hoekstra, Johan Kon, Tamás Péni, Maarten Schoukens, Roland Tóth
2025	J	`jnl`	Orthogonal-by-construction augmentation of physics-based input-output models. CoRR Bendegúz M. Györök, Maarten Schoukens, Tamás Péni, Roland Tóth
2025	J	`jnl`	Port-Hamiltonian Neural Networks with Output Error Noise Models. CoRR Sarvin Moradi, Gerben Izaak Beintema, Nick O. Jaensson, Roland Tóth, Maarten Schoukens
2024	J	`jnl`	A frequency-domain approach for estimating continuous-time diffusively coupled linear networks. CoRR Desen Liang, E. M. M. Kivits, Maarten Schoukens, Paul M. J. Van den Hof
2024	J	`jnl`	Baseline Results for Selected Nonlinear System Identification Benchmarks. CoRR Max D. Champneys, Gerben Izaak Beintema, Roland Tóth, Maarten Schoukens, Timothy J. Rogers
2024	—	`conf`	Koopman Data-Driven Predictive Control with Robust Stability and Recursive Feasibility Guarantees. CDC Thomas de Jong, Valentina Breschi, Maarten Schoukens, Mircea Lazar
2024	J	`jnl`	Koopman Data-Driven Predictive Control with Robust Stability and Recursive Feasibility Guarantees. CoRR Thomas de Jong, Valentina Breschi, Maarten Schoukens, Mircea Lazar
2024	J	`jnl`	Koopman form of nonlinear systems with inputs. Autom. Lucian-Cristian Iacob, Roland Tóth, Maarten Schoukens
2024	J	`jnl`	Learning Subsystem Dynamics in Nonlinear Systems via Port-Hamiltonian Neural Networks. CoRR G. J. E. van Otterdijk, Sarvin Moradi, Siep Weiland, Roland Tóth, Nick O. Jaensson, Maarten Schoukens
2024	J	`jnl`	Learning-based model augmentation with LFRs. CoRR Jan H. Hoekstra, Chris Verhoek, Roland Tóth, Maarten Schoukens
2024	—	`conf`	Measurements and System Identification for the Characterization of Smooth Muscle Cell Dynamics. MeMeA Dilan Öztürk, Pepijn Saraber, Kevin Bielawski, Alessandro Giudici, Leon Schurgers, Koen D. Reesink, Maarten Schoukens
2024	J	`jnl`	Measurements and System Identification for the Characterization of Smooth Muscle Cell Dynamics. CoRR Dilan Öztürk, Pepijn Saraber, Kevin Bielawski, Alessandro Giudici, Leon Schurgers, Koen D. Reesink, Maarten Schoukens
2024	J	`jnl`	Meta-state-space learning: An identification approach for stochastic dynamical systems. Autom. Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth
2024	J	`jnl`	Physics-Guided State-Space Model Augmentation Using Weighted Regularized Neural Networks. CoRR Yuhan Liu, Roland Tóth, Maarten Schoukens
2024	J	`jnl`	Space-Filling Input Design for Nonlinear State-Space Identification. CoRR Máté Kiss, Roland Tóth, Maarten Schoukens
2024	J	`jnl`	State Derivative Normalization for Continuous-Time Deep Neural Networks. CoRR Jonas Weigand, Gerben Izaak Beintema, Jonas Ulmen, Daniel Görges, Roland Tóth, Maarten Schoukens, Martin Ruskowski
2023	J	`jnl`	Automated multi-objective system identification using grammar-based genetic programming. Autom. Dhruv Khandelwal, Maarten Schoukens, Roland Tóth
2023	—	`conf`	Computationally Efficient Predictive Control Based on ANN State-Space Models. CDC Jan H. Hoekstra, Bence Cseppento, Gerben Izaak Beintema, Maarten Schoukens, Zsolt Kollár, Roland Tóth
2023	J	`jnl`	Computationally efficient predictive control based on ANN state-space models. CoRR Jan H. Hoekstra, Bence Cseppento, Gerben Izaak Beintema, Maarten Schoukens, Zsolt Kollár, Roland Tóth
2023	A*	`conf`	Continuous-time identification of dynamic state-space models by deep subspace encoding. ICLR Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth
2023	J	`jnl`	Data-Driven Model-Reference Control With Closed-Loop Stability: The Output-Feedback Case. IEEE Control. Syst. Lett. T. O. de Jong, Valentina Breschi, Maarten Schoukens, Simone Formentin
2023	J	`jnl`	Deep subspace encoders for nonlinear system identification. Autom. Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth
2023	J	`jnl`	Finite Dimensional Koopman Form of Polynomial Nonlinear Systems. CoRR Lucian-Cristian Iacob, Maarten Schoukens, Roland Tóth
2023	J	`jnl`	Initialization Approach for Nonlinear State-Space Identification via the Subspace Encoder Approach. CoRR Rishi Ramkannan, Gerben Izaak Beintema, Roland Tóth, Maarten Schoukens
2023	J	`jnl`	Meta-State-Space Learning: An Identification Approach for Stochastic Dynamical Systems. CoRR Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth
2023	—	`conf`	Nonlinear Data-Driven Predictive Control Using Deep Subspace Prediction Networks. CDC Mircea Lazar, Mihai-Serban Popescu, Maarten Schoukens
2023	J	`jnl`	Physics-Informed Learning Using Hamiltonian Neural Networks with Output Error Noise Models. CoRR Sarvin Moradi, Nick O. Jaensson, Roland Tóth, Maarten Schoukens
2022	J	`jnl`	A Data-driven Pricing Scheme for Optimal Routing through Artificial Currencies. CoRR David van de Sanden, Maarten Schoukens, Mauro Salazar
2022	J	`jnl`	Deep Subspace Encoders for Nonlinear System Identification. CoRR Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth
2022	J	`jnl`	Deep subspace encoders for continuous-time state-space identification. CoRR Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth
2022	—	`conf`	Deep-Learning-Based Identification of LPV Models for Nonlinear Systems. CDC Chris Verhoek, Gerben Izaak Beintema, Sofie Haesaert, Maarten Schoukens, Roland Tóth
2022	J	`jnl`	Deep-Learning-Based Identification of LPV Models for Nonlinear Systems. CoRR Chris Verhoek, Gerben Izaak Beintema, Sofie Haesaert, Maarten Schoukens, Roland Tóth
2022	J	`jnl`	Koopman Form of Nonlinear Systems with Inputs. CoRR Lucian-Cristian Iacob, Roland Tóth, Maarten Schoukens
2022	—	`conf`	Message Passing-based System Identification for NARMAX Models. CDC Albert Podusenko, Semih Akbayrak, Ismail Senöz, Maarten Schoukens, Wouter M. Kouw
2022	—	`conf`	NARX Identification using Derivative-Based Regularized Neural Networks. CDC L. H. Peeters, Gerben Izaak Beintema, Marco Forgione, Maarten Schoukens
2022	J	`jnl`	NARX Identification using Derivative-Based Regularized Neural Networks. CoRR L. H. Peeters, Gerben Izaak Beintema, Marco Forgione, Maarten Schoukens
2022	J	`jnl`	Optimal Synthesis of LTI Koopman Models for Nonlinear Systems with Inputs. CoRR Lucian-Cristian Iacob, Roland Tóth, Maarten Schoukens
2022	C	`conf`	Variational message passing for online polynomial NARMAX identification. ACC Wouter M. Kouw, Albert Podusenko, Magnus T. Koudahl, Maarten Schoukens
2022	J	`jnl`	Variational message passing for online polynomial NARMAX identification. CoRR Wouter M. Kouw, Albert Podusenko, Magnus T. Koudahl, Maarten Schoukens
2021	—	`conf`	Deep Identification of Nonlinear Systems in Koopman Form. CDC Lucian-Cristian Iacob, Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth
2021	J	`jnl`	Deep Identification of Nonlinear Systems in Koopman Form. CoRR Lucian-Cristian Iacob, Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth
2021	J	`jnl`	Feedback identification of conductance-based models. Autom. Thiago B. Burghi, Maarten Schoukens, Rodolphe Sepulchre
2021	J	`jnl`	Identification of the nonlinear steering dynamics of an autonomous vehicle. CoRR Gábor Rödönyi, Gerben Izaak Beintema, Roland Tóth, Maarten Schoukens, Daniel Pup, Ádám Kisari, Zs. Vígh, Péter Korös, Alexandros Soumelidis, József Bokor
2021	—	`conf`	Improved Initialization of State-Space Artificial Neural Networks. ECC Maarten Schoukens
2021	J	`jnl`	Improved Initialization of State-Space Artificial Neural Networks. CoRR Maarten Schoukens
2021	—	`conf`	Nonlinear state-space identification using deep encoder networks. L4DC Gerben Beintema, Roland Tóth, Maarten Schoukens
2020	J	`jnl`	A Tree Adjoining Grammar Representation for Models Of Stochastic Dynamical Systems. CoRR Dhruv Khandelwal, Maarten Schoukens, Roland Tóth
2020	J	`jnl`	A Tree Adjoining Grammar representation for models of stochastic dynamical systems. Autom. Dhruv Khandelwal, Maarten Schoukens, Roland Tóth
2020	J	`jnl`	Best Linear Approximation of Nonlinear Continuous-Time Systems Subject to Process Noise and Operating in Feedback. CoRR Rik Pintelon, Maarten Schoukens, John Lataire
2020	J	`jnl`	Best Linear Approximation of Nonlinear Continuous-Time Systems Subject to Process Noise and Operating in Feedback. IEEE Trans. Instrum. Meas. Rik Pintelon, Maarten Schoukens, John Lataire
2020	J	`jnl`	Extending the Best Linear Approximation Framework to the Process Noise Case. IEEE Trans. Autom. Control. Maarten Schoukens, Rik Pintelon, Tadeusz P. Dobrowiecki, Johan Schoukens
2020	J	`jnl`	Feedback Identification of conductance-based models. CoRR Thiago B. Burghi, Maarten Schoukens, Rodolphe Sepulchre
2020	J	`jnl`	Feedback for nonlinear system identification. CoRR Thiago B. Burghi, Maarten Schoukens, Rodolphe Sepulchre
2020	J	`jnl`	Non-linear State-space Model Identification from Video Data using Deep Encoders. CoRR Gerben Izaak Beintema, Roland Tóth, Maarten Schoukens
2020	J	`jnl`	Nonlinear state-space identification using deep encoder networks. CoRR Gerben Beintema, Roland Tóth, Maarten Schoukens
2020	J	`jnl`	On the Initialization of Nonlinear LFR Model Identification with the Best Linear Approximation. CoRR Maarten Schoukens, Roland Tóth
2020	—	`conf`	System identification of biophysical neuronal models. CDC Thiago B. Burghi, Maarten Schoukens, Rodolphe Sepulchre
2020	J	`jnl`	System identification of biophysical neuronal models. CoRR Thiago B. Burghi, Maarten Schoukens, Rodolphe Sepulchre
2020	J	`jnl`	Toolbox for Discovering Dynamic System Relations via TAG Guided Genetic Programming. CoRR Stefan-Cristian Nechita, Roland Tóth, Dhruv Khandelwal, Maarten Schoukens
2019	B	`conf`	Data-driven Modelling of Dynamical Systems Using Tree Adjoining Grammar and Genetic Programming. CEC Dhruv Khandelwal, Maarten Schoukens, Roland Tóth
2019	J	`jnl`	Data-driven Modelling of Dynamical Systems Using Tree Adjoining Grammar and Genetic Programming. CoRR Dhruv Khandelwal, Maarten Schoukens, Roland Tóth
2019	—	`conf`	Feedback for nonlinear system identification. ECC Thiago B. Burghi, Maarten Schoukens, Rodolphe Sepulchre
2019	—	`conf`	Grammar-based Representation and Identification of Dynamical Systems. ECC Dhruv Khandelwal, Maarten Schoukens, Roland Tóth
2019	J	`jnl`	Sampled-data adaptive observer for state-affine systems with uncertain output equation. Autom. Tarek Ahmed-Ali, Koen Tiels, Maarten Schoukens, Fouad Giri
2018	J	`jnl`	Comparison of several data-driven nonlinear system identification methods on a simplified glucoregulatory system example. CoRR Anna Marconato, Maarten Schoukens, Koen Tiels, Widanalage Dhammika Widanage, Amjad Abu-Rmileh, Johan Schoukens
2018	J	`jnl`	Extending the Best Linear Approximation Framework to the Process Noise Case. CoRR Maarten Schoukens, Rik Pintelon, Tadeusz P. Dobrowiecki, Johan Schoukens
2018	J	`jnl`	Fast Identification of Wiener-Hammerstein Systems using Discrete Optimization. CoRR Maarten Schoukens, Gerd Vandersteen, Yves Rolain, Francesco Ferranti
2018	J	`jnl`	From Nonlinear Identification to Linear Parameter Varying Models: Benchmark Examples. CoRR Maarten Schoukens, Roland Tóth
2018	J	`jnl`	Grammar-based Representation and Identification of Dynamical Systems. CoRR Dhruv Khandelwal, Maarten Schoukens, Roland Tóth
2018	J	`jnl`	Linear Parameter Varying Representation of a class of MIMO Nonlinear Systems. CoRR Maarten Schoukens, Roland Tóth
2018	—	`conf`	On the Simulation of Polynomial NARMAX Models. CDC Dhruv Khandelwal, Maarten Schoukens, Roland Tóth
2018	J	`jnl`	On the Simulation of Polynomial NARMAX Models. CoRR Dhruv Khandelwal, Maarten Schoukens, Roland Tóth
2018	J	`jnl`	Structure Discrimination in Block-Oriented Models Using Linear Approximations: A Theoretic Framework. CoRR Johan Schoukens, Rik Pintelon, Yves Rolain, Maarten Schoukens, Koen Tiels, Laurent Vanbeylen, Anne Van Mulders, Gerd Vandersteen
2018	J	`jnl`	Structure detection of Wiener-Hammerstein systems with process noise. CoRR Erliang Zhang, Maarten Schoukens, Johan Schoukens
2017	J	`jnl`	Identification of block-oriented nonlinear systems starting from linear approximations: A survey. Autom. Maarten Schoukens, Koen Tiels
2017	J	`jnl`	Parametric identification of parallel Wiener-Hammerstein systems. CoRR Maarten Schoukens, Anna Marconato, Rik Pintelon, Gerd Vandersteen, Yves Rolain
2017	J	`jnl`	Structure Detection of Wiener-Hammerstein Systems With Process Noise. IEEE Trans. Instrum. Meas. Erliang Zhang, Maarten Schoukens, Johan Schoukens
2016	—	`conf`	Filter interpretation of regularized impulse response modeling. ECC Anna Marconato, Maarten Schoukens, Johan Schoukens
2016	J	`jnl`	Filter-based regularisation for impulse response modelling. CoRR Anna Marconato, Maarten Schoukens, Johan Schoukens
2016	J	`jnl`	Identification of Nonlinear Block-Oriented Systems starting from Linear Approximations: A Survey. CoRR Maarten Schoukens, Koen Tiels
2016	J	`jnl`	Initial estimates for Wiener-Hammerstein models using phase-coupled multisines. CoRR Koen Tiels, Maarten Schoukens, Johan Schoukens
2016	J	`jnl`	Obtaining the Pre-Inverse of a Power Amplifier using Iterative Learning Control. CoRR Maarten Schoukens, Jules Hammenecker, Adam Cooman
2015	—	`conf`	Decoupling static nonlinearities in a parallel Wiener-Hammerstein system: A first-order approach. I2MTC Philippe Dreesen, Maarten Schoukens, Koen Tiels, Johan Schoukens
2015	J	`jnl`	Initial estimates for Wiener-Hammerstein models using phase-coupled multisines. Autom. Koen Tiels, Maarten Schoukens, Johan Schoukens
2015	J	`jnl`	Parametric identification of parallel Wiener-Hammerstein systems. Autom. Maarten Schoukens, Anna Marconato, Rik Pintelon, Gerd Vandersteen, Yves Rolain
2015	J	`jnl`	Structure discrimination in block-oriented models using linear approximations: A theoretic framework. Autom. Johan Schoukens, Rik Pintelon, Yves Rolain, Maarten Schoukens, Koen Tiels, Laurent Vanbeylen, Anne Van Mulders, Gerd Vandersteen
2014	J	`jnl`	Identification of Wiener-Hammerstein systems by a nonparametric separation of the best linear approximation. Autom. Maarten Schoukens, Rik Pintelon, Yves Rolain
2014	—	`conf`	System identification in a real world. AMC Johan Schoukens, Anna Marconato, Rik Pintelon, Yves Rolain, Maarten Schoukens, Koen Tiels, Laurent Vanbeylen, Gerd Vandersteen, Anne Van Mulders
2013	—	`conf`	An identification algorithm for parallel Wiener-Hammerstein systems. CDC Maarten Schoukens, Gerd Vandersteen, Yves Rolain
2013	—	`conf`	Combining the Best Linear Approximation and Dimension Reduction to Identify the Linear Blocks of Parallel Wiener Systems. ALCOSP Maarten Schoukens, Christian Lyzell, Martin Enqvist
2013	—	`conf`	Study of the effective number of parameters in nonlinear identification benchmarks. CDC Anna Marconato, Maarten Schoukens, Yves Rolain, Johan Schoukens
2012	J	`jnl`	Cross-term Elimination in Parallel Wiener Systems Using a Linear Input Transformation. IEEE Trans. Instrum. Meas. Maarten Schoukens, Yves Rolain
2012	J	`jnl`	Parametric Identification of Parallel Wiener Systems. IEEE Trans. Instrum. Meas. Maarten Schoukens, Yves Rolain
2011	J	`jnl`	Parametric Identification of Parallel Hammerstein Systems. IEEE Trans. Instrum. Meas. Maarten Schoukens, Rik Pintelon, Yves Rolain
2011	—	`conf`	Parametric MIMO parallel Wiener identification. CDC/ECC Maarten Schoukens, Yves Rolain