| A ProM Operational Support Provider for Predictive Monitoring of Business Processes. M Federici, W Rizzi, C Di Francescomarino, M Dumas, C Ghidini, ... BPM (Demos), 1-5, 2015 | 12 | 2015 |
| Alarm-Based Prescriptive Process Monitoring I Teinemaa, N Tax, M de Leoni, M Dumas, FM Maggi International Conference on Business Process Management 329, 91-107, 2018 | 54 | 2018 |
| An experimental evaluation of the generalizing capabilities of process discovery techniques and black-box sequence models N Tax, SJ van Zelst, I Teinemaa Enterprise, Business-Process and Information Systems Modeling: 19th …, 2018 | 13 | 2018 |
| An interdisciplinary comparison of sequence modeling methods for next-element prediction N Tax, I Teinemaa, SJ van Zelst Software and Systems Modeling 19 (6), 1345-1365, 2020 | 65 | 2020 |
| Automatic Playlist Continuation through a Composition of Collaborative Filters I Teinemaa, N Tax, C Bentes arXiv preprint arXiv:1808.04288, 2018 | 2 | 2018 |
| BPIC 2015: Diagnostics of building permit application process in dutch municipalities I Teinemaa, A Leontjeva, KO Masing BPI Challenge Report 72, 2015 | 17 | 2015 |
| Clustering-based predictive process monitoring C Di Francescomarino, M Dumas, FM Maggi, I Teinemaa IEEE transactions on services computing 12 (6), 896-909, 2016 | 201 | 2016 |
| Community-based prediction of activity change in Skype I Teinemaa, A Leontjeva, M Dumas, R Kikas Proceedings of the 2015 IEEE/ACM International Conference on Advances in …, 2015 | 6 | 2015 |
| Community-Based Prediction of Activity Decay in a Social Network I Teinemaa University of Tartu, 2014 | | 2014 |
| Comparison of Security Risk-oriented Modelling Languages: BPMN vs. Secure Tropos I Teinemaa | | |
| Encoding resource experience for predictive process monitoring J Kim, M Comuzzi, M Dumas, FM Maggi, I Teinemaa Decision Support Systems 153, 113669, 2022 | 26 | 2022 |
| Fire now, fire later: alarm-based systems for prescriptive process monitoring SA Fahrenkrog-Petersen, N Tax, I Teinemaa, M Dumas, M Leoni, ... Knowledge and Information Systems 64 (2), 559-587, 2022 | 54 | 2022 |
| Learning when to treat business processes: Prescriptive process monitoring with causal inference and reinforcement learning ZD Bozorgi, M Dumas, ML Rosa, A Polyvyanyy, M Shoush, I Teinemaa International Conference on Advanced Information Systems Engineering, 364-380, 2023 | 7 | 2023 |
| Learning When to Treat Business Processes: Prescriptive Process Monitoring with Causal Inference and Reinforcement Learning Z Dasht Bozorgi, M Dumas, M La Rosa, A Polyvyanyy, M Shoush, ... arXiv e-prints, arXiv: 2303.03572, 2023 | | 2023 |
| Outcome-oriented predictive process monitoring: review and benchmark I Teinemaa, M Dumas, M La Rosa, FM Maggi ACM Transactions on Knowledge Discovery in Data 13 (2), 17:1-17:57, 2019 | 347 | 2019 |
| Personalization in practice: Methods and applications D Goldenberg, K Kofman, J Albert, S Mizrachi, A Horowitz, I Teinemaa Proceedings of the 14th ACM international conference on web search and data …, 2021 | 47 | 2021 |
| Predictive and Prescriptive Monitoring of Business Process Outcomes. I Teinemaa, B Depaire BPM (PhD/Demos), 15-19, 2019 | 8 | 2019 |
| Predictive business process monitoring with structured and unstructured data I Teinemaa, M Dumas, FM Maggi, C Di Francescomarino Business Process Management: 14th International Conference, BPM 2016, Rio de …, 2016 | 130 | 2016 |
| Prescriptive process monitoring based on causal effect estimation Z Dasht Bozorgi, I Teinemaa, M Dumas, M La Rosa, A Polyvyanyy | | 2023 |
| Prescriptive process monitoring based on causal effect estimation ZD Bozorgi, I Teinemaa, M Dumas, M La Rosa, A Polyvyanyy Information Systems 116, 102198, 2023 | 16 | 2023 |
Marlon DumasProfessor at University of Tartu | Chief Product Officer at ApromoreVerified email at ut.ee