Social Analytics of Team Interaction using Dynamic Complexity Heat Maps and Network Visualizations. - Travis J. Wiltshire; Dan Hudson 001; Philia Lijdsman; Stijn Wever; Martin Atzmueller (CoRR, 2020)

Local Exceptionality Detection in Time Series Using Subgroup Discovery: An Approach Exemplified on Team Interaction Data. - Dan Hudson 001; Travis J. Wiltshire; Martin Atzmueller (DS, 2021)

Examining Team Interaction using Dynamic Complexity and Network Visualizations. - Travis J. Wiltshire; Dan Hudson 001; Max Belitsky; Philia Lijdsman; Stijn Wever; Martin Atzmueller (ICHMS, 2021)

Human Interaction and Networking Transitions System (HINTS) for Social User Analytics and Modeling of Offline Team Group Interaction Information. - Ngoc N. T. Doan; Dan Hudson 001; Travis J. Wiltshire; Philia Lijdsman; Stijn Wever; Martin Atzmueller (UMAP (Adjunct Publication), 2021)

Local Exceptionality Detection in Time Series Using Subgroup Discovery. - Dan Hudson 001; Travis J. Wiltshire; Martin Atzmueller (CoRR, 2021)

Visualization Methods for Exploratory Subgroup Discovery on Time Series Data. - Dan Hudson 001; Travis J. Wiltshire; Martin Atzmueller (IWINAC (1), 2022)

Hyperparameter Analysis of Wide-Kernel CNN Architectures in Industrial Fault Detection - An Exploratory Study. - Jurgen van den Hoogen; Dan Hudson 001; Stefan Bloemheuvel; Martin Atzmueller (DSAA, 2023)

Enhanced Explanations for Knowledge-Augmented Clustering using Subgroup Discovery. - Maciej Szelazek; Dan Hudson 001; Szymon Bobek; Grzegorz J. Nalepa; Martin Atzmueller (DSAA, 2023)

Subgroup Discovery with SD4Py. - Dan Hudson 001; Martin Atzmueller (ECAI Workshops (1), 2023)

Explainable Multi-Modal and Local Approaches to Modelling Injuries in Sports Data. - Dan Hudson 001; Ruud J. R. Den Hartigh; L. Rens A. Meerhoff; Martin Atzmueller (ICDM (Workshops), 2023)

Data-Hungry Fault Detection Algorithms Can Try Transfer Learning for Starters. - Jurgen van den Hoogen; Dan Hudson 001; Martin Atzmueller (ICDEW, 2024)

Graph Signal Processing Unearths the Best Locations for Soil Moisture Sensors. - Jurgen van den Hoogen; Dan Hudson 001; Martin Atzmueller (ICMLA, 2024)

Stay Tuned! Analysing Hyperparameters of a Wide-Kernel Architecture for Industrial Faults. - Dan Hudson 001; Jurgen van den Hoogen; Stefan Bloemheuvel; Martin Atzmueller (CAI, 2024)

Tailoring the Hyperparameters of a Wide-Kernel Convolutional Neural Network to Fit Different Bearing Fault Vibration Datasets. - Dan Hudson 001; Jurgen van den Hoogen; Martin Atzmueller (CoRR, 2024)

Finding One's Bearings in the Hyperparameter Landscape of a Wide-Kernel Convolutional Fault Detector. - Dan Hudson 001; Jurgen van den Hoogen; Martin Atzmueller (IEEE Access, 2026)

A comparison of graph construction techniques for applying graph signal processing to soil moisture networks. - Jurgen van den Hoogen; Dan Hudson 001; Martin Atzmueller (Discov. Comput., 2026)