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Jeroen J. Jansen
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2020 – today
- 2024
- [j12]Tim Offermans, Ewa Szymanska, Francisco Alexandre A. Souza, Jeroen J. Jansen:
Process expert knowledge is essential in creating value from data-driven industrial soft sensors. Comput. Chem. Eng. 183: 108602 (2024) - 2023
- [j11]Francisco Souza
, Tim Offermans
, Ruud Barendse, Geert J. Postma, Jeroen J. Jansen:
Contextual Mixture of Experts: Integrating Knowledge into Predictive Modeling. IEEE Trans. Ind. Informatics 19(8): 9048-9059 (2023) - [i3]Mahdiyeh Ghaffari, Mickey C. J. Lukkien, Nematollah Omidikia, Gerjen H. Tinnevelt, Marcel C. P. van Eijk, Jeroen J. Jansen:
Systematic reduction of Hyperspectral Images for high-throughput Plastic Characterization. CoRR abs/2308.14776 (2023) - [i2]Mahdiyeh Ghaffari, Gerjen H. Tinnevelt, Marcel C. P. van Eijk, Stanislav Podchezertsev, Geert J. Postma, Jeroen J. Jansen:
Mono/Multi-material Characterization Using Hyperspectral Images and Multi-Block Non-Negative Matrix Factorization. CoRR abs/2309.12329 (2023) - 2022
- [j10]Leonardo Galvis, Tim Offermans
, Carlo G. Bertinetto, Andrea Carnoli, Emina Karamujic, Weiwei Li, Ewa Szymanska, Lutgarde M. C. Buydens, Jeroen J. Jansen:
Retrospective quality by design r(QbD) for lactose production using historical process data and design of experiments. Comput. Ind. 141: 103696 (2022) - [c1]Francisco Souza, Tim Offermans
, Jeroen J. Jansen:
Batch Endpoint Prediction using Local Mixture of Batch Time Experts. MetroXRAINE 2022: 613-617 - [i1]Francisco Souza, Tim Offermans, Ruud Barendse, Geert J. Postma, Jeroen J. Jansen:
Contextual Mixture of Experts: Integrating Knowledge into Predictive Modeling. CoRR abs/2211.00558 (2022) - 2021
- [j9]Tim Offermans
, Ewa Szymanska, Geert H. van Kollenburg
, Lutgarde M. C. Buydens, Jeroen J. Jansen:
Automatically optimizing dynamic synchronization of individual industrial process variables for statistical modelling. Comput. Chem. Eng. 152: 107402 (2021) - [j8]Geert H. van Kollenburg
, Roel Bouman, Tim Offermans
, Jan Gerretzen, Lutgarde M. C. Buydens, Henk-Jan van Manen, Jeroen J. Jansen:
Process PLS: Incorporating substantive knowledge into the predictive modelling of multiblock, multistep, multidimensional and multicollinear process data. Comput. Chem. Eng. 154: 107466 (2021) - 2020
- [j7]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:
Understanding chemical production processes by using PLS path model parameters as soft sensors. Comput. Chem. Eng. 139: 106841 (2020) - [j6]Tim Offermans
, Ewa Szymanska, Lutgarde M. C. Buydens, Jeroen J. Jansen:
Synchronizing process variables in time for industrial process monitoring and control. Comput. Chem. Eng. 140: 106938 (2020) - [j5]Feven Desta
, Mike Buxton, Jeroen J. Jansen:
Fusion of Mid-Wave Infrared and Long-Wave Infrared Reflectance Spectra for Quantitative Analysis of Minerals. Sensors 20(5): 1472 (2020)
2010 – 2019
- 2012
- [j4]Age K. Smilde
, Marieke E. Timmerman, Margriet M. W. B. Hendriks, Jeroen J. Jansen, Huub C. J. Hoefsloot:
Generic framework for high-dimensional fixed-effects ANOVA. Briefings Bioinform. 13(5): 524-535 (2012)
2000 – 2009
- 2009
- [j3]Jeroen J. Jansen, Nicole M. van Dam
, Huub C. J. Hoefsloot, Age K. Smilde
:
Crossfit analysis: a novel method to characterize the dynamics of induced plant responses. BMC Bioinform. 10: 425 (2009) - 2005
- [j2]Age K. Smilde
, Jeroen J. Jansen, Huub C. J. Hoefsloot, Robert-Jan A. N. Lamers, Jan van der Greef, Marieke E. Timmerman:
ANOVA-simultaneous component analysis (ASCA): a new tool for analyzing designed metabolomics data. Bioinform. 21(13): 3043-3048 (2005) - 2004
- [j1]Jeroen J. Jansen, Huub C. J. Hoefsloot, Hans F. M. Boelens, Jan van der Greef, Age K. Smilde
:
Analysis of longitudinal metabolomics data. Bioinform. 20(15): 2438-2446 (2004)
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