Koen Tiels - RankMe

58 papers A 1Journal 43Unranked 14

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Generalizable models of magnetic hysteresis via physics-aware recurrent neural networks. Comput. Phys. Commun. Abhishek Chandra, Taniya Kapoor, Bram Daniels, Mitrofan Curti, Koen Tiels, Daniel M. Tartakovsky, Elena A. Lomonova
2025	J	`jnl`	Neuro-Symbolic Operator for Interpretable and Generalizable Characterization of Complex Piezoelectric Systems. CoRR Abhishek Chandra, Taniya Kapoor, Mitrofan Curti, Koen Tiels, Elena A. Lomonova
2025	J	`jnl`	Safety and Optimality in Learning-Based Control at Low Computational Cost. IEEE Trans. Autom. Control. Dominik Baumann, Krzysztof Kowalczyk, Cristian R. Rojas, Koen Tiels, Pawel Wachel
2025	J	`jnl`	Safety and optimality in learning-based control at low computational cost. CoRR Dominik Baumann, Krzysztof Kowalczyk, Cristian R. Rojas, Koen Tiels, Pawel Wachel
2025	J	`jnl`	Self-Calibrating Position Measurements: Applied to Imperfect Hall Sensors. CoRR Max van Meer, Marijn van Noije, Koen Tiels, Enzo Evers, Lennart Blanken, Gert Witvoet, Tom Oomen
2025	—	`conf`	Truncated Gaussian Noise Estimation in State-Space Models. CDC Rodrigo A. González, Angel L. Cedeño, Koen Tiels, Tom Oomen
2025	J	`jnl`	Truncated Gaussian Noise Estimation in State-Space Models. CoRR Rodrigo A. González, Angel L. Cedeño, Koen Tiels, Tom Oomen
2024	J	`jnl`	Kernel-based identification using Lebesgue-sampled data. Autom. Rodrigo A. González, Koen Tiels, Tom Oomen
2024	J	`jnl`	Magnetic Hysteresis Modeling with Neural Operators. CoRR Abhishek Chandra, Bram Daniels, Mitrofan Curti, Koen Tiels, Elena A. Lomonova
2023	—	`conf`	A Computationally Lightweight Safe Learning Algorithm. CDC Dominik Baumann, Krzysztof Kowalczyk, Koen Tiels, Pawel Wachel
2023	J	`jnl`	A Wavelet-Based Approach to FRF Identification From Incomplete Data. IEEE Trans. Instrum. Meas. Nic Dirkx, Koen Tiels, Tom Oomen
2023	J	`jnl`	A computationally lightweight safe learning algorithm. CoRR Dominik Baumann, Krzysztof Kowalczyk, Koen Tiels, Pawel Wachel
2023	J	`jnl`	Discovering Sparse Hysteresis Models: A Data-driven Study for Piezoelectric Materials and Perspectives on Magnetic Hysteresis. CoRR Abhishek Chandra, Bram Daniels, Mitrofan Curti, Koen Tiels, Elena A. Lomonova, Daniel M. Tartakovsky
2023	J	`jnl`	Identifying Lebesgue-sampled Continuous-time Impulse Response Models: A Kernel-based Approach. CoRR Rodrigo A. González, Koen Tiels, Tom Oomen
2023	—	`conf`	Iterative Robust Experiment Design for MIMO System Identification via the S-Lemma. CCTA Nic Dirkx, Koen Tiels, Tom Oomen
2023	J	`jnl`	Kernel-based identification using Lebesgue-sampled data. CoRR Rodrigo A. González, Koen Tiels, Tom Oomen
2023	J	`jnl`	Learning low-dimensional separable decompositions of MIMO non-linear systems. Int. J. Control Pawel Wachel, Koen Tiels, Maciej Filinski
2023	J	`jnl`	Memory-Element-Based Hysteresis: Identification and Compensation of a Piezoelectric Actuator. IEEE Trans. Control. Syst. Technol. Nard Strijbosch, Koen Tiels, Tom Oomen
2023	J	`jnl`	Neural oscillators for magnetic hysteresis modeling. CoRR Abhishek Chandra, Taniya Kapoor, Bram Daniels, Mitrofan Curti, Koen Tiels, Daniel M. Tartakovsky, Elena A. Lomonova
2022	J	`jnl`	Decoupling multivariate functions using a nonparametric filtered tensor decomposition. CoRR Jan Decuyper, Koen Tiels, Siep Weiland, Mark C. Runacres, Johan Schoukens
2022	J	`jnl`	Hysteresis Feedforward Compensation: A Direct Tuning Approach Using Hybrid-MEM-Elements. IEEE Control. Syst. Lett. Nard Strijbosch, Koen Tiels, Tom Oomen
2022	—	`conf`	Physics-informed neural networks for modelling anisotropic and bi-anisotropic electromagnetic constitutive laws through indirect data. SSCI Abhishek Chandra, Mitrofan Curti, Koen Tiels, Elena A. Lomonova, Daniel M. Tartakovsky
2021	J	`jnl`	Decoupling multivariate functions using a non-parametric Filtered CPD approach. CoRR Jan Decuyper, Koen Tiels, Siep Weiland, Johan Schoukens
2021	—	`conf`	Low-Dimensional Decompositions for Nonlinear Finite Impulse Response Modeling. ICCS (5) Maciej Filinski, Pawel Wachel, Koen Tiels
2021	J	`jnl`	PNLSS Toolbox 1.0. CoRR Jan Decuyper, Koen Tiels, Johan Schoukens
2020	J	`jnl`	A nonlinear model of vortex-induced forces on an oscillating cylinder in a fluid flow. CoRR Jan Decuyper, Tim De Troyer, Koen Tiels, Johan Schoukens, Mark C. Runacres
2020	A	`conf`	Beyond exploding and vanishing gradients: analysing RNN training using attractors and smoothness. AISTATS Antônio H. Ribeiro, Koen Tiels, Luis Antonio Aguirre, Thomas B. Schön
2020	J	`jnl`	On the smoothness of nonlinear system identification. Autom. Antônio H. Ribeiro, Koen Tiels, Jack Umenberger, Thomas B. Schön, Luis Antonio Aguirre
2020	J	`jnl`	Retrieving highly structured models starting from black-box nonlinear state-space models using polynomial decoupling. CoRR Jan Decuyper, Koen Tiels, Mark C. Runacres, Johan Schoukens
2019	J	`jnl`	Decoupling Multivariate Polynomials for Nonlinear State-Space Models. IEEE Control. Syst. Lett. Jan Decuyper, Philippe Dreesen, Johan Schoukens, Mark Runacres, Koen Tiels
2019	—	`conf`	Deep Convolutional Networks in System Identification. CDC Carl R. Andersson, Antônio H. Ribeiro, Koen Tiels, Niklas Wahlström, Thomas B. Schön
2019	J	`jnl`	Deep Convolutional Networks in System Identification. CoRR Carl R. Andersson, Antônio H. Ribeiro, Koen Tiels, Niklas Wahlström, Thomas B. Schön
2019	J	`jnl`	On the Smoothness of Nonlinear System Identification. CoRR Antônio H. Ribeiro, Koen Tiels, Jack Umenberger, Thomas B. Schön, Luis Antonio Aguirre
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
2019	J	`jnl`	The trade-off between long-term memory and smoothness for recurrent networks. CoRR Antônio H. Ribeiro, Koen Tiels, Luis Antonio Aguirre, Thomas B. Schön
2018	J	`jnl`	A Local Polynomial Approach to Nonparametric Estimation of the Best Linear Approximation of Lithium-Ion Battery From Multiple Datasets. CoRR Rishi Relan, Koen Tiels, Jean-Marc Timmermans, Johan Schoukens
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`	Data driven discrete-time parsimonious identification of a nonlinear state-space model for a weakly nonlinear system with short data record. CoRR Rishi Relan, Koen Tiels, Anna Marconato, Philippe Dreesen, Johan Schoukens
2018	J	`jnl`	Hammerstein system identification through best linear approximation inversion and regularisation. Int. J. Control Ricardo Castro-Garcia, Koen Tiels, Oscar Mauricio Agudelo, Johan A. K. Suykens
2018	J	`jnl`	Nonlinear state-space modelling of the kinematics of an oscillating circular cylinder in a fluid flow. CoRR Jan Decuyper, Tim De Troyer, Mark Runacres, Koen Tiels, Johan Schoukens
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
2017	J	`jnl`	A Local Polynomial Approach to Nonparametric Estimation of the Best Linear Approximation of Lithium-Ion Battery From Multiple Datasets. IEEE Control. Syst. Lett. Rishi Relan, Koen Tiels, Jean-Marc Timmermans, Johan Schoukens
2017	J	`jnl`	Identification of block-oriented nonlinear systems starting from linear approximations: A survey. Autom. Maarten Schoukens, Koen Tiels
2017	—	`conf`	Nonlinear system identification: Finding structure in nonlinear black-box models. CAMSAP Philippe Dreesen, Koen Tiels, Mariya Ishteva, Johan Schoukens
2017	J	`jnl`	Parameter reduction in nonlinear state-space identification of hysteresis. CoRR Alireza Fakhrizadeh Esfahani, Philippe Dreesen, Koen Tiels, Jean-Philippe Noël, Johan Schoukens
2016	—	`conf`	Hammerstein system identification using LS-SVM and steady state time response. ECC Ricardo Castro-Garcia, Oscar Mauricio Agudelo, Koen Tiels, Johan A. K. Suykens
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`	Wiener system identification with generalized orthonormal basis functions. CoRR Koen Tiels, Johan Schoukens
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	—	`conf`	Incorporating Best Linear Approximation within LS-SVM-based Hammerstein System Identification. CDC Ricardo Castro-Garcia, Koen Tiels, Johan Schoukens, Johan A. K. Suykens
2015	J	`jnl`	Initial estimates for Wiener-Hammerstein models using phase-coupled multisines. Autom. Koen Tiels, Maarten Schoukens, Johan Schoukens
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	—	`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
2014	J	`jnl`	Wiener system identification with generalized orthonormal basis functions. Autom. Koen Tiels, Johan Schoukens
2013	—	`conf`	From coupled to decoupled polynomial representations in parallel Wiener-Hammerstein models. CDC Koen Tiels, Johan Schoukens
2013	—	`conf`	Iterative Update of the Pole Locations in a Wiener-Schetzen Model. ALCOSP Koen Tiels, Johan Schoukens
2011	—	`conf`	Identifying a Wiener system using a variant of the Wiener G-Functionals. CDC/ECC Koen Tiels, Johan Schoukens