| Issue Date | Title | Author(s) |
| 2021 | A Computational Framework for Modeling Complex Sensor Network Data Using Graph Signal Processing and Graph Neural Networks in Structural Health Monitoring. | Bloemheuvel, Stefan; van den Hoogen, Jurgen; Atzmueller, Martin |
| 2023 | Advanced Analytics on Complex Industrial Data | van den Hoogen, Jurgen; Bloemheuvel, Stefan; Atzmueller, Martin |
| 2021 | Classifying Multivariate Signals in Rolling Bearing Fault Detection Using Adaptive Wide-Kernel CNNs | van den Hoogen, Jurgen; Bloemheuvel, Stefan; Atzmueller, Martin |
| 2020 | Complex Network Modeling of Supply and Demand Data: An Application Case in the Plastics Recycling Industry (Abstract) | Bloemheuvel, Stefan; van den Hoogen, Jurgen; Atzmueller, Martin |
| 2019 | Enhancing Sequential Pattern Mining Explainability with Markov Chain Probabilities | |
| 2023 | Graph construction on complex spatiotemporal data for enhancing graph neural network-based approaches | Bloemheuvel, Stefan; van den Hoogen, Jurgen; Atzmueller, Martin |
| 2022 | Graph neural networks for multivariate time series regression with application to seismic data | Bloemheuvel, Stefan; van den Hoogen, Jurgen; Jozinovic, Dario; Michelini, Alberto; Atzmueller, Martin |
| 2023 | Hyperparameter analysis of wide-kernel CNN architectures in industrial fault detection: an exploratory study | van den Hoogen, Jurgen; Hudson, Dan; Bloemheuvel, Stefan; Atzmueller, Martin |
| 2022 | Multivariate Time Series Regression with Graph Neural Networks | Bloemheuvel, Stefan; van den Hoogen, Jurgen; Jozinovic, Dario; Michelini, Alberto; Atzmueller, Martin |
| 2022 | Rapid prediction of ground shaking intensity with Graph Neural Networks | |
| 2019 | The Di-Plast Data Science Toolkit – Enabling a Smart Data-Driven Digital Circular Economy for the Plastics Industry | |
HOCHSCHULBIBLIOGRAPHIE