Controlling Rayleigh-Bénard convection via Reinforcement Learning. - Gerben Beintema; Alessandro Corbetta; Luca Biferale; Federico Toschi (CoRR, 2020)

Non-linear State-space Model Identification from Video Data using Deep Encoders. - Gerben Izaak Beintema; Roland Tóth; Maarten Schoukens (CoRR, 2020)

Deep Identification of Nonlinear Systems in Koopman Form. - Lucian-Cristian Iacob; Gerben Izaak Beintema; Maarten Schoukens; Roland Tóth (CDC, 2021)

Nonlinear state-space identification using deep encoder networks. - Gerben Beintema; Roland Tóth; Maarten Schoukens (L4DC, 2021)

Identification of the nonlinear steering dynamics of an autonomous vehicle. - Gábor Rödönyi; Gerben Izaak Beintema; Roland Tóth; Maarten Schoukens; Daniel Pup; Ádám Kisari; Zs. Vígh; Péter Korös; Alexandros Soumelidis; József Bokor (CoRR, 2021)

NARX Identification using Derivative-Based Regularized Neural Networks. - L. H. Peeters; Gerben Izaak Beintema; Marco Forgione; Maarten Schoukens (CDC, 2022)

Deep-Learning-Based Identification of LPV Models for Nonlinear Systems. - Chris Verhoek; Gerben Izaak Beintema; Sofie Haesaert; Maarten Schoukens; Roland Tóth (CDC, 2022)

Deep subspace encoders for continuous-time state-space identification. - Gerben Izaak Beintema; Maarten Schoukens; Roland Tóth (CoRR, 2022)

Computationally Efficient Predictive Control Based on ANN State-Space Models. - Jan H. Hoekstra; Bence Cseppento; Gerben Izaak Beintema; Maarten Schoukens; Zsolt Kollár; Roland Tóth (CDC, 2023)

Continuous-time identification of dynamic state-space models by deep subspace encoding. - Gerben Izaak Beintema; Maarten Schoukens; Roland Tóth (ICLR, 2023)

Initialization Approach for Nonlinear State-Space Identification via the Subspace Encoder Approach. - Rishi Ramkannan; Gerben Izaak Beintema; Roland Tóth; Maarten Schoukens (CoRR, 2023)

Deep subspace encoders for nonlinear system identification. - Gerben Izaak Beintema; Maarten Schoukens; Roland Tóth (Autom., 2023)

Meta-state-space learning: An identification approach for stochastic dynamical systems. - Gerben Izaak Beintema; Maarten Schoukens; Roland Tóth (Autom., 2024)

State Derivative Normalization for Continuous-Time Deep Neural Networks. - Jonas Weigand; Gerben Izaak Beintema; Jonas Ulmen; Daniel Görges; Roland Tóth; Maarten Schoukens; Martin Ruskowski (CoRR, 2024)

Baseline Results for Selected Nonlinear System Identification Benchmarks. - Max D. Champneys; Gerben Izaak Beintema; Roland Tóth; Maarten Schoukens; Timothy J. Rogers 003 (CoRR, 2024)

Port-Hamiltonian Neural Networks with Output Error Noise Models. - Sarvin Moradi; Gerben Izaak Beintema; Nick Jaensson; Roland Tóth; Maarten Schoukens (CoRR, 2025)

Learning Koopman Models From Data Under General Noise Conditions. - Lucian-Cristian Iacob; Máté Szécsi; Gerben Izaak Beintema; Maarten Schoukens; Roland Tóth (CoRR, 2025)