How Much Event Data Is Enough? A Statistical Framework for Process Discovery. - Martin Bauer 006; Arik Senderovich; Avigdor Gal; Lars Grunske; Matthias Weidlich 001 (CAiSE, 2018)

ELPaaS: Event Log Privacy as a Service. - Martin Bauer 006; Stephan A. Fahrenkrog-Petersen; Agnes Koschmider; Felix Mannhardt; Han van der Aa; Matthias Weidlich 001 (BPM (PhD/Demos), 2019)

Estimating Process Conformance by Trace Sampling and Result Approximation. - Martin Bauer 006; Han van der Aa; Matthias Weidlich 001 (EMISA Forum, 2020)

Representativeness of Event Data in Conformance Checking. - Martin Kabierski (BPM (PhD/Demos), 2021)

Privacy-Aware Process Performance Indicators: Framework and Release Mechanisms. - Martin Kabierski; Stephan A. Fahrenkrog-Petersen; Matthias Weidlich 001 (CAiSE, 2021)

SaCoFa: Semantics-aware Control-flow Anonymization for Process Mining. - Stephan A. Fahrenkrog-Petersen; Martin Kabierski; Fabian Rösel; Han van der Aa; Matthias Weidlich 001 (ICPM, 2021)

Sampling What Matters: Relevance-guided Sampling of Event Logs. - Martin Kabierski; Hoang Lam Nguyen; Lars Grunske; Matthias Weidlich 001 (ICPM, 2021)

PaPPI: Privacy-aware Process Performance Indicators (Extended Abstract). - Martin Kabierski; Stephan A. Fahrenkrog-Petersen; Glenn Dittmann; Matthias Weidlich 001 (ICPM Doctoral Consortium / Demo, 2022)

Privacy-Preserving Process Mining with PM4Py (Extended Abstract). - Henrik Kirchmann; Stephan A. Fahrenkrog-Petersen; Martin Kabierski; Han van der Aa; Matthias Weidlich 001 (ICPM Doctoral Consortium / Demo, 2022)

Sampling and approximation techniques for efficient process conformance checking. - Martin Bauer 006; Han van der Aa; Matthias Weidlich 001 (Inf. Syst., 2022)

Model-Independent Error Bound Estimation for Conformance Checking Approximation. - Mohammadreza Fani Sani; Martin Kabierski; Sebastiaan J. van Zelst; Wil M. P. van der Aalst (Business Process Management Workshops, 2023)

Addressing the Log Representativeness Problem using Species Discovery. - Martin Kabierski; Markus Richter; Matthias Weidlich 001 (ICPM, 2023)

Hiding in the forest: Privacy-preserving process performance indicators. - Martin Kabierski; Stephan A. Fahrenkrog-Petersen; Matthias Weidlich 001 (Inf. Syst., 2023)

Semantics-aware mechanisms for control-flow anonymization in process mining. - Stephan A. Fahrenkrog-Petersen; Martin Kabierski; Han van der Aa; Matthias Weidlich 001 (Inf. Syst., 2023)

SpeciAL4PM: Species Analysis of Event Logs for Process Mining. - Martin Kabierski; Christian Imenkamp; Agnes Koschmider; Matthias Weidlich 001 (BPM (Demos / Resources Forum), 2024)

Addressing the Log Representativeness Problem using Species Discovery (Extended Abstract). - Martin Kabierski; Markus Richter; Matthias Weidlich 001 (EMISA, 2024)

A Classification of Data Quality Issues in Object-Centric Event Data. - Maike Basmer; Martin Kabierski; Kristina Sahling; Agnieszka Patecka; Saimir Bala; Jan Mendling (ICPM Workshops, 2024)

Determining Window Sizes Using Species Estimation for Accurate Process Mining over Streams. - Christian Imenkamp; Martin Kabierski; Hendrik Reiter; Matthias Weidlich 001; Wilhelm Hasselbring; Agnes Koschmider (CAiSE (1), 2025)

Quantifying and relating the completeness and diversity of process representations using species estimation. - Martin Kabierski; Markus Richter; Matthias Weidlich 001 (Inf. Syst., 2025)