Black swan: augmenting statistics with event data. - Johannes Lorey; Felix Naumann; Benedikt Forchhammer; Andrina Mascher; Peter Retzlaff; Armin Zamani Farahani; Soeren Discher; Cindy Faehnrich; Stefan Lemme; Thorsten Papenbrock; Robert Christoph Peschel; Stephan Richter 003; et al. (CIKM, 2011)

Duplicate Detection on GPUs. - Benedikt Forchhammer; Thorsten Papenbrock; Thomas Stening; Sven Viehmeier; Uwe Draisbach; Felix Naumann (BTW, 2013)

Ein Datenbankkurs mit 6000 Teilnehmern - Erfahrungen auf der openHPI MOOC Plattform. - Felix Naumann; Maximilian Jenders; Thorsten Papenbrock (Inform. Spektrum, 2014)

Scaling Out the Discovery of Inclusion Dependencies. - Sebastian Kruse 001; Thorsten Papenbrock; Felix Naumann (BTW, 2015)

Data Profiling with Metanome. - Thorsten Papenbrock; Tanja Bergmann; Moritz Finke; Jakob Zwiener; Felix Naumann (Proc. VLDB Endow., 2015)

Functional Dependency Discovery: An Experimental Evaluation of Seven Algorithms. - Thorsten Papenbrock; Jens Ehrlich; Jannik Marten; Tommy Neubert; Jan-Peer Rudolph; Martin Schönberg; Jakob Zwiener; Felix Naumann (Proc. VLDB Endow., 2015)

Divide & Conquer-based Inclusion Dependency Discovery. - Thorsten Papenbrock; Sebastian Kruse 001; Jorge-Arnulfo Quiané-Ruiz; Felix Naumann (Proc. VLDB Endow., 2015)

Progressive Duplicate Detection. - Thorsten Papenbrock; Arvid Heise; Felix Naumann (IEEE Trans. Knowl. Data Eng., 2015)

Approximate Discovery of Functional Dependencies for Large Datasets. - Tobias Bleifuß; Susanne Bülow; Johannes Frohnhofen; Julian Risch; Georg Wiese; Sebastian Kruse 001; Thorsten Papenbrock; Felix Naumann (CIKM, 2016)

Holistic Data Profiling: Simultaneous Discovery of Various Metadata. - Jens Ehrlich; Mandy Roick; Lukas Schulze; Jakob Zwiener; Thorsten Papenbrock; Felix Naumann (EDBT, 2016)

RDFind: Scalable Conditional Inclusion Dependency Discovery in RDF Datasets. - Sebastian Kruse 001; Anja Jentzsch; Thorsten Papenbrock; Zoi Kaoudi; Jorge-Arnulfo Quiané-Ruiz; Felix Naumann (SIGMOD Conference, 2016)

A Hybrid Approach to Functional Dependency Discovery. - Thorsten Papenbrock; Felix Naumann (SIGMOD Conference, 2016)

Data Anamnesis: Admitting Raw Data into an Organization. - Sebastian Kruse 001; Thorsten Papenbrock; Hazar Harmouch; Felix Naumann (IEEE Data Eng. Bull., 2016)

Fast Approximate Discovery of Inclusion Dependencies. - Sebastian Kruse 001; Thorsten Papenbrock; Christian Dullweber; Moritz Finke; Manuel Hegner; Martin Zabel; Christian Zöllner 002; Felix Naumann (BTW, 2017)

A Hybrid Approach for Efficient Unique Column Combination Discovery. - Thorsten Papenbrock; Felix Naumann (BTW, 2017)

Data-driven Schema Normalization. - Thorsten Papenbrock; Felix Naumann (EDBT, 2017)

Data Profiling - Effiziente Entdeckung Struktureller Abhängigkeiten. - Thorsten Papenbrock (Ausgezeichnete Informatikdissertationen, 2017)

Detecting Inclusion Dependencies on Very Many Tables. - Fabian Tschirschnitz; Thorsten Papenbrock; Felix Naumann (ACM Trans. Database Syst., 2017)

Data profiling - efficient discovery of dependencies (Profilerstellung für Daten - Effiziente Entdeckung von Abhängigkeiten) - Thorsten Papenbrock (2017)

Data Profiling - Ziawasch Abedjan; Lukasz Golab; Felix Naumann; Thorsten Papenbrock (Morgan & Claypool Publishers, 2018)

Data Profiling - Effiziente Entdeckung Struktureller Abhängigkeiten. - Thorsten Papenbrock (BTW, 2019)

An Actor Database System for Akka. - Sebastian Schmidl; Frederic Schneider; Thorsten Papenbrock (BTW (Workshops), 2019)

Inclusion Dependency Discovery: An Experimental Evaluation of Thirteen Algorithms. - Falco Dürsch; Axel Stebner; Fabian Windheuser; Maxi Fischer; Tim Friedrich; Nils Strelow; Tobias Bleifuß; Hazar Harmouch; Lan Jiang 001; Thorsten Papenbrock; Felix Naumann (CIKM, 2019)

DynFD: Functional Dependency Discovery in Dynamic Datasets. - Philipp Schirmer; Thorsten Papenbrock; Sebastian Kruse 001; Felix Naumann; Dennis Hempfing; Torben Mayer; Daniel Neuschäfer-Rube (EDBT, 2019)

Hitting Set Enumeration with Partial Information for Unique Column Combination Discovery. - Johann Birnick; Thomas Bläsius; Tobias Friedrich 001; Felix Naumann; Thorsten Papenbrock; Martin Schirneck (Proc. VLDB Endow., 2020)

MDedup: Duplicate Detection with Matching Dependencies. - Ioannis K. Koumarelas; Thorsten Papenbrock; Felix Naumann (Proc. VLDB Endow., 2020)

Efficient Discovery of Matching Dependencies. - Philipp Schirmer; Thorsten Papenbrock; Ioannis K. Koumarelas; Felix Naumann (ACM Trans. Database Syst., 2020)

Optimized Theta-Join Processing. - Julian Weise; Sebastian Schmidl; Thorsten Papenbrock (BTW, 2021)

Relational Header Discovery using Similarity Search in a Table Corpus. - Hazar Harmouch; Thorsten Papenbrock; Felix Naumann (ICDE, 2021)

Front Matter. - Hannes Mühleisen; Thorsten Papenbrock (Proc. VLDB Endow., 2021)

Distributed detection of sequential anomalies in univariate time series. - Johannes Schneider 003; Phillip Wenig; Thorsten Papenbrock (VLDB J., 2021)

Workload-driven, Lazy Discovery of Data Dependencies for Query Optimization. - Jan Kossmann; Felix Naumann; Daniel Lindner; Thorsten Papenbrock (CIDR, 2022)

DataGossip: A Data Exchange Extension for Distributed Machine Learning Algorithms. - Phillip Wenig; Thorsten Papenbrock (EDBT, 2022)

Anomaly Detection in Time Series: A Comprehensive Evaluation. - Sebastian Schmidl; Phillip Wenig; Thorsten Papenbrock (Proc. VLDB Endow., 2022)

TimeEval: A Benchmarking Toolkit for Time Series Anomaly Detection Algorithms. - Phillip Wenig; Sebastian Schmidl; Thorsten Papenbrock (Proc. VLDB Endow., 2022)

Data dependencies for query optimization: a survey. - Jan Kossmann; Thorsten Papenbrock; Felix Naumann (VLDB J., 2022)

Efficient distributed discovery of bidirectional order dependencies. - Sebastian Schmidl; Thorsten Papenbrock (VLDB J., 2022)

HYPEX: Hyperparameter Optimization in Time Series Anomaly Detection. - Sebastian Schmidl; Phillip Wenig; Thorsten Papenbrock (BTW, 2023)

DPQL: The Data Profiling Query Language. - Marcian Seeger; Sebastian Schmidl; Alexander Vielhauer; Thorsten Papenbrock (BTW, 2023)

A Few Models to Rule Them All: Aggregating Machine Learning Models. - Florian Siepe; Phillip Wenig; Thorsten Papenbrock (LWDA, 2023)

Actix-Telepathy. - Phillip Wenig; Thorsten Papenbrock (REBLS@SPLASH, 2023)

Correction to: Data dependencies for query optimization: a survey. - Jan Kossmann; Thorsten Papenbrock; Felix Naumann (VLDB J., 2023)

Series2Graph++: Distributed Detection of Correlation Anomalies in Multivariate Time Series. - Phillip Wenig; Thorsten Papenbrock (DaWaK, 2024)

Anomaly Detectors for Multivariate Time Series: The Proof of the Pudding is in the Eating. - Phillip Wenig; Sebastian Schmidl; Thorsten Papenbrock (ICDEW, 2024)

Discovering Functional Dependencies through Hitting Set Enumeration. - Tobias Bleifuß; Thorsten Papenbrock; Thomas Bläsius; Martin Schirneck; Felix Naumann (Proc. ACM Manag. Data, 2024)

AutoTSAD: Unsupervised Holistic Anomaly Detection for Time Series Data. - Sebastian Schmidl; Felix Naumann; Thorsten Papenbrock (Proc. VLDB Endow., 2024)

DPQL: Applications for Holistic Data Profiling. - Marcian Seeger; Thorsten Papenbrock (BTW, 2025)