Publications

Christoph Augenstein, Theo Zschörnig, Norman Spangenberg, Robert Wehlitz, and Bogdan Franczyk. A generic architectural framework for machine learning on data streams. Enterprise Information Systems, 97--114, Springer International Publishing, Cham, 2020.

Negin Malekian, Amay A. Agrawal, Thomas U. Berendonk, Ali Al-Fatlawi, and Michael Schroeder. A genome-wide scan of wastewater E. coli for genes under positive selection: focusing on mechanisms of antibiotic resistance. Scientific Reports, (12)1Springer Science and Business Media LLC, May 2022. [PUMA: imported topic_lifescience] URL

Jannik Irmai, Shengxian Zhao, Jannik Presberger, and Bjoern Andres. A Graph Multi-separator Problem for Image Segmentation. arXiv, 2023. [PUMA: topic_visualcomputing]

Lennart J. Schulze, Sachin K. Thekke Veettil, and Ivo F. Sbalzarini. A high-order fully Lagrangian particle level-set method for dynamic surfaces. CoRR, (abs/2306.07986)2023. [PUMA: imported topic_lifescience]

Martin Pippel, David Jebb, Franziska Patzold, Sylke Winkler, Heiko Vogel, Gene Myers, Michael Hiller, and Anna K Hundsdoerfer. A highly contiguous genome assembly of the bat hawkmoth Hyles vespertilio (Lepidoptera: Sphingidae). Gigascience, (9)1Oxford University Press (OUP), January 2020. [PUMA: genome comparison hawkmoth-silk gene annotation; moth topic_lifescience reads; long assembly; PacBio]

Piotr Ostropolski-Nalewaja, Jerzy Marcinkowski, David Carral, and Sebastian Rudolph. A Journey to the Frontiers of Query Rewritability. CoRR, (abs/2012.11269)2020. [PUMA: imported] URL

Lukas Gienapp, Wolfgang Kircheis, Bjarne Sievers, Benno Stein, and Martin Potthast. A large dataset of scientific text reuse in Open-Access publications. Scientific Data, (10)1:58, Nature Publishing Group UK London, 2023. [PUMA: imported topic_language]

Langxuan Su, and Sayan Mukherjee. A large deviation approach to posterior consistency in dynamical systems. arXiv, 2021.

Tom Richard Vargis, and Siavash Ghiasvand. A Light-weight and Unsupervised Method for Near Real-time Behavioral Analysis using Operational Data Measurement. 2024. [PUMA: imported livinglab] URL

David Schaller, Marc Hellmuth, and Peter Stadler. A Linear-Time Algorithm for the Common Refinement of Rooted Phylogenetic Trees on a Common Leaf Set. July 2021. [PUMA: imported]

Matti Wiegmann, Jan Heinrich Reimer, Maximilian Ernst, Martin Potthast, Matthias Hagen, and Benno Stein. A Mastodon Corpus to Evaluate Federated Microblog Search. In Sheikh Farzana, Maik Fröbe, Michael Granitzer, Gijs Hendriksen, Djoerd Hiemstra, Martin Potthast, and Saber Zerhoudi (Eds.), Proceedings of the First International Workshop on Open Web Search (WOWS 2024), (3689):37--49, CEUR Workshop Proceedings, March 2024. [PUMA: topic_language topic_lifescience] URL

Johannes Gerritzen, Andreas Hornig, Peter Winkler, and Maik Gude. A methodology for direct parameter identification for experimental results using machine learning—Real world application to the highly non-linear deformation behavior of FRP. Computational Materials Science, (244):113274, Elsevier, 2024. [PUMA: FRP area_architectures using experimental deformation direct learning application identification world parameter machine Real topic_engineering results highly non-linear behavior]

Martin Grimmer, Martin Max Röhling, Dennis Kreußel, and Simon Ganz. A Modern and Sophisticated Host Based Intrusion Detection Data Set. 2019. [PUMA: imported] URL

Jakob Bossek, Pascal Kerschke, and Heike Trautmann. A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms. Appl. Soft Comput., (88)105901:105901, Elsevier BV, March 2020.

Bian Li, Jeffrey Mendenhall, John A Capra, and Jens Meiler. A multitask deep-learning method for predicting membrane associations and secondary structures of proteins. J. Proteome Res., (20)8:4089--4100, American Chemical Society (ACS), August 2021. [PUMA: multitask convolutional prediction; memory transmembrane deep learning; neural networks; topology long short-term structure secondary topic_lifescience prediction]

Bian Li, Jeffrey Mendenhall, John A. Capra, and Jens Meiler. A Multitask Deep-Learning Method for Predicting Membrane Associations and Secondary Structures of Proteins. Journal of Proteome Research, (20)8:4089–4100, American Chemical Society (ACS), July 2021. [PUMA: imported topic_lifescience] URL

Minh Triet Chau, Diego Esteves, and Jens Lehmann. A Neural-based model to Predict the Future Natural Gas Market Price through Open-domain Event Extraction. CLEOPATRA@ESWC, 2020.

Khalid Al Khatib, Michael Voelske, Anh Le, Shahbaz Syed, Martin Potthast, and Benno Stein. A New Dataset for Causality Identification in Argumentative Texts. Proceedings of the 24th Meeting of the Special Interest Group on Discourse and Dialogue, 349–354, Association for Computational Linguistics, 2023. [PUMA: imported topic_language] URL

Satyadharma Tirtarasa, and Anni-Yasmin Turhan. A New Dimension to Generalization: Computing Temporal EL Concepts from Positive Examples (Extended Abstract). Description Logics, 2022. [PUMA: imported topic_knowledge] URL

Sam DeLuca, and Jens Meiler. A Novel Method for Guiding Protein-Ligand Docking with QSAR-Derived Pharmacophore Maps. Biophysical Journal, (100)3:394a–395a, Elsevier BV, February 2011. [PUMA: imported topic_lifescience] URL