Feedforward Control in the Presence of Input Nonlinearities: A Learning-based Approach. - Jilles van Hulst; Maurice Poot; Dragan Kostic; Kai Wa Yan; Jim Portegies; Tom Oomen (CoRR, 2022)

Estimation of Dynamic Gaussian Processes. - Jilles van Hulst; Roy van Zuijlen; Duarte Antunes; W. P. Maurice H. Heemels (CDC, 2023)

Bayesian Estimation for Linear Systems with Nonlinear Output and General Noise Distribution Using Fourier Basis Functions. - R. A. C. van Zuijlen; J. S. van Hulst; W. P. M. H. Heemels; Duarte J. Antunes (CDC, 2023)

Data-Efficient Quadratic Q-Learning Using LMIs. - J. S. van Hulst; W. P. M. H. Heemels; Duarte J. Antunes (CDC, 2024)

Automatic Basis Function Selection in Iterative Learning Control: A Sparsity-Promoting Approach Applied to an Industrial Printer. - Tjeerd Ickenroth; Max van Haren; Johan Kon; Max van Meer; Jilles van Hulst; Tom Oomen (ACC, 2025)

Calibration of Electron Microscopes Through Deep Learning and Bayesian Optimization. - Jilles van Hulst; R. A. C. van Zuijlen; Narges Javaheri; Maurits Diephuis; Duarte J. Antunes; W. P. M. H. Heemels (IEEE Access, 2025)

Smart Exploration in Reinforcement Learning using Bounded Uncertainty Models. - J. S. van Hulst; W. P. M. H. Heemels; Duarte J. Antunes (CoRR, 2025)