| Understanding chemical production processes by using PLS path model parameters as soft sensors GH van Kollenburg, J van Es, J Gerretzen, H Lanters, R Bouman, ... Computers & Chemical Engineering 139, 106841, 2020 | 21 | 2020 |
| Process PLS: Incorporating substantive knowledge into the predictive modelling of multiblock, multistep, multidimensional and multicollinear process data G van Kollenburg, R Bouman, T Offermans, J Gerretzen, L Buydens, ... Computers & Chemical Engineering 154, 107466, 2021 | 16 | 2021 |
| Automated flow cytometric identification of disease-specific cells by the ECLIPSE algorithm R Folcarelli, S Van Staveren, R Bouman, B Hilvering, GH Tinnevelt, ... Scientific reports 8 (1), 10907, 2018 | 15 | 2018 |
| Unsupervised anomaly detection algorithms on real-world data: how many do we need? R Bouman, Z Bukhsh, T Heskes Journal of Machine Learning Research 25 (105), 1-34, 2024 | 12 | 2024 |
| Data, software and scripts related to the Process PLS methodology manuscript GH van Kollenburg, R Bouman, T Offermans, J Jansen Mendeley Data, 2020 | 2 | 2020 |
| Acquiring better load estimates by combining anomaly and change-point detection in power grid time-series measurements R Bouman, L Schmeitz, L Buise, J Heres, Y Shapovalova, T Heskes Sustainable Energy, Grids and Networks, 101540, 2024 | | 2024 |
| A comparison of anomaly detection algorithms with applications on recoater streaking in an additive manufacturing process R Stribos, R Bouman, L Jimenez, M Slot, M Stoelinga Rapid Prototyping Journal, 2024 | | 2024 |
| Improving space weather analysis using Spark Structured Streaming R Bouman Radboud University, 2020 | | 2020 |
Tom HeskesProfessor of Computer Science and Artificial Intelligence, Radboud University NijmegenПотвърден имейл адрес: science.ru.nl
