Understanding chemical production processes by using PLS path model parameters as soft sensors. - Geert H. van Kollenburg; Jacoline van Es; Jan Gerretzen; Heleen Lanters; Roel Bouman; Willem Koelewijn; Anthony N. Davies; Lutgarde M. C. Buydens; Henk-Jan van Manen; Jeroen J. Jansen (Comput. Chem. Eng., 2020)

Process PLS: Incorporating substantive knowledge into the predictive modelling of multiblock, multistep, multidimensional and multicollinear process data. - Geert H. van Kollenburg; Roel Bouman; Tim Offermans; Jan Gerretzen; Lutgarde M. C. Buydens; Henk-Jan van Manen; Jeroen J. Jansen (Comput. Chem. Eng., 2021)

Acquiring Better Load Estimates by Combining Anomaly and Change-point Detection in Power Grid Time-series Measurements. - Roel Bouman; Linda Schmeitz; Luco Buise; Jacco Heres; Yuliya Shapovalova; Tom Heskes (CoRR, 2024)

Unsupervised Anomaly Detection Algorithms on Real-world Data: How Many Do We Need? - Roel Bouman; Zaharah Bukhsh; Tom Heskes (J. Mach. Learn. Res., 2024)

Autoencoders for Anomaly Detection are Unreliable. - Roel Bouman; Tom Heskes (CoRR, 2025)