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Recent publications

  1. Training Machine Learning Models to Detect Group Differences in Neuro…

    Guglielmo, G., Wiltshire, T., & Louwerse, M. (Accepted/In press). Training Machine Learning Models to Detect Group Differences in Neurophysiological Data Using Recurrence Quantification Analysis Based Features. In 14th International Conference on Agents and Artificial Intelligence (ICAART)
  2. Human Interaction and Networking Transitions System (HINTS) for Socia…

    Doan, N., Hudson, D., Wiltshire, T., Lijdsman, P., Wever, S., & Atzmueller, M. (2021). Human Interaction and Networking Transitions System (HINTS) for Social User Analytics and Modeling of Offline Team Group Interaction Information. In Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization (UMAP '21 Adjunct) https://camps.aptaracorp.com/ACM_PMS/PMS/ACM/UMAP21ADJUNCT/29/680f25d7-a38f-11eb-8d84-166a08e17233/OUT/umap21adjunct-29.pdf
  3. Team Coordination Dynamics: A Review on Using Wearable Technology to …

    Halgas, E., van Eijndhoven, K., Gevers, J., Wiltshire, T., Westerink, J., & Rispens, S. (2021). Team Coordination Dynamics: A Review on Using Wearable Technology to Assess Team Functioning and Team Performance. Poster session presented at 16th Annual Conference of the Interdisciplinary Network for Group Research .
  4. Comparing Methods to Quantify Multivariate Synchrony with multiSyncPy…

    Hudson, D., Wiltshire, T., & Atzmueller, M. (2021). Comparing Methods to Quantify Multivariate Synchrony with multiSyncPy, using Simulated Noise, Kuramoto Oscillators and Human Movement Data. Poster session presented at Conference on Complex Systems 2021, Lyon, France.
  5. Local Exceptionality Detection in Time Series using Subgroup Discovery

    Hudson, D., Wiltshire, T., & Atzmueller, M. (2021). Local Exceptionality Detection in Time Series using Subgroup Discovery. In Proceedings of the 24th International Conference on Discovery Science (pp. 435-335)

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