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- V. Pasquadibisceglie, A. Appice, G. Castellano, D. Malerba, Predictive Process Mining Meets Computer Vision. BPM (Forum) 2020: 176-192, https://link.springer.com/chapter/10.1007/978-3-030-58638-6_11
- A. Appice, P. Ardimento, D. Malerba, G. Modugno, D. Marra, M. Mottola, Training in a Virtual Learning Environment: A Process Mining Approach. EAIS 2020: 1-8 IEEE, https://ieeexplore.ieee.org/document/9122760
- V. Pasquadibisceglie, A. Appice, G. Castellano, D. Malerba and G. Modugno, ORANGE: Outcome-Oriented Predictive Process Monitoring Based on Image Encoding and CNNs, in IEEE Access, vol. 8, pp. 184073-184086, 2020, doi: 10.1109/ACCESS.2020.3029323
- V. Pasquadibisceglie, A. Appice, G. Castellano, D. Malerba, A multi-view deep learning approach for predictive business process monitoring, IEEE TRANSACTIONS ON SERVICES COMPUTING, IEEE, 2021 https://ieeexplore.ieee.org/document/9325056
- N. Di Mauro, A. Appice, T.m.A. Basile T.M.A. Activity Prediction of Business Process Instances with Inception CNN Models. In: AI*IA 2019 – Advances in Artificial Intelligence. AI*IA 2019. LNCS 11946. Springer, Cham, https://doi.org/10.1007/978-3-030-35166-3_25
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