Logic Based Look-Ahead for the Execution of Multi-perspective Declarative Processes. - Martin Käppel; Nicolai Schützenmeier; Stefan Schönig; Lars Ackermann; Stefan Jablonski (BPMDS/EMMSAD@CAiSE, 2019)

Detection of Declarative Process Constraints in LTL Formulas. - Nicolai Schützenmeier; Martin Käppel; Sebastian Petter; Stefan Schönig; Stefan Jablonski (EOMAS@CAiSE, 2019)

A Comparative Study for the Selection of Machine Learning Algorithms based on Descriptive Parameters. - Chettan Kumar; Martin Käppel; Nicolai Schützenmeier; Philipp Eisenhuth; Stefan Jablonski (DATA, 2019)

Cost-Sensitive Predictive Business Process Monitoring. - Martin Käppel; Stefan Jablonski; Stefan Schönig (ADBIS (Short Papers), 2021)

Upper-Bounded Model Checking for Declarative Process Models. - Nicolai Schützenmeier; Martin Käppel; Sebastian Petter; Stefan Jablonski (PoEM, 2021)

Evaluating Predictive Business Process Monitoring Approaches on Small Event Logs. - Martin Käppel; Stefan Jablonski; Stefan Schönig (QUATIC, 2021)

Leveraging Small Sample Learning for Business Process Management. - Martin Käppel; Stefan Schönig; Stefan Jablonski (Inf. Softw. Technol., 2021)

Language-independent look-ahead for checking multi-perspective declarative process models. - Martin Käppel; Lars Ackermann; Stefan Schönig; Stefan Jablonski (Softw. Syst. Model., 2021)

Deviance Analysis by Means of Redescription Mining. - Martin Käppel; Engjëll Ahmeti; Stefan Jablonski (BPMDS/EMMSAD@CAiSE, 2022)

Bridging Research Fields: An Empirical Study on Joint, Neural Relation Extraction Techniques. - Lars Ackermann; Julian Neuberger; Martin Käppel; Stefan Jablonski (CAiSE, 2023)

Model-Agnostic Event Log Augmentation for Predictive Process Monitoring. - Martin Käppel; Stefan Jablonski (CAiSE, 2023)

Scenario-Based Model Checking of Declarative Process Models. - Nicolai Schützenmeier; Martin Käppel; Myriel Fichtner; Stefan Jablonski (ICEIS (2), 2023)

Comparing the Expressiveness of Imperative and Declarative Process Models. - Nicolai Schützenmeier; Stefan Jablonski; Martin Käppel; Lars Ackermann (MOBA, 2023)

Automaton-based comparison of Declare process models. - Nicolai Schützenmeier; Martin Käppel; Lars Ackermann; Stefan Jablonski; Sebastian Petter (Softw. Syst. Model., 2023)

Correction: Automaton-based comparison of Declare process models. - Nicolai Schützenmeier; Martin Käppel; Lars Ackermann; Stefan Jablonski; Sebastian Petter (Softw. Syst. Model., 2023)

Attention Please: What Transformer Models Really Learn for Process Prediction. - Martin Käppel; Lars Ackermann; Stefan Jablonski; Simon Härtl (BPM, 2024)

TeaPie: A Tool for Efficient Annotation of Process Information Extraction Data. - Julian Neuberger; Jannic Herrmann; Martin Käppel; Han van der Aa; Stefan Jablonski (CoopIS, 2024)

Recent Advances in Data-Driven Business Process Management. - Lars Ackermann; Martin Käppel; Laura Marcus; Linda Moder; Sebastian Dunzer; Markus Hornsteiner; Annina Liessmann; Yorck Zisgen; Philip Empl; Lukas-Valentin Herm; Nicolas Neis; Julian Neuberger; et al. (CoRR, 2024)

Redescription mining-based business process deviance analysis. - Engjëll Ahmeti; Martin Käppel; Stefan Jablonski (Softw. Syst. Model., 2024)

A Human-in-the-Loop Approach for Improving Fairness in Predictive Business Process Monitoring. - Martin Käppel; Julian Neuberger; Felix Möhrlein; Sven Weinzierl; Martin Matzner; Stefan Jablonski (BPM, 2025)

From Source to Target: Leveraging Transfer Learning for Predictive Process Monitoring in Organizations. - Sven Weinzierl; Sandra Zilker; Annina Liessmann; Martin Käppel; Weixin Wang; Martin Matzner (CoRR, 2025)