Publications

Nacira Abbas, Kholoud Alghamdi, Mortaza Alinam, Francesca Alloatti, Glenda Amaral, Claudia d'Amato, Luigi Asprino, Martin Beno, Felix Bensmann, Russa Biswas, Ling Cai, Riley Capshaw, Valentina Anita Carriero, Irene Celino, Amine Dadoun, Stefano De Giorgis, Harm Delva, John Domingue, Michel Dumontier, Vincent Emonet, Marieke van Erp, Paola Espinoza Arias, Omaima Fallatah, Sebastián Ferrada, Marc Gallofré Ocaña, Michalis Georgiou, Genet Asefa Gesese, Frances Gillis-Webber, Francesca Giovannetti, Mar\`ıa Granados Buey, Ismail Harrando, Ivan Heibi, Vitor Horta, Laurine Huber, Federico Igne, Mohamad Yaser Jaradeh, Neha Keshan, Aneta Koleva, Bilal Koteich, Kabul Kurniawan, Mengya Liu, Chuangtao Ma, Lientje Maas, Martin Mansfield, Fabio Mariani, Eleonora Marzi, Sepideh Mesbah, Maheshkumar Mistry, Alba Catalina Morales Tirado, Anna Nguyen, Viet Bach Nguyen, Allard Oelen, Valentina Pasqual, Heiko Paulheim, Axel Polleres, Margherita Porena, Jan Portisch, Valentina Presutti, Kader Pustu-Iren, Ariam Rivas Mendez, Soheil Roshankish, Sebastian Rudolph, Harald Sack, Ahmad Sakor, Jaime Salas, Thomas Schleider, Meilin Shi, Gianmarco Spinaci, Chang Sun, Tabea Tietz, Molka Tounsi Dhouib, Alessandro Umbrico, Wouter van den Berg, and Weiqin Xu. Knowledge Graphs evolution and preservation -- A technical report from ISWS 2019. arXiv, 2020. [PUMA: topic_lifescience]

Abdelrahman Abdelkawi, Hamid Zafar, Maria Maleshkova, and Jens Lehmann. Complex query augmentation for question answering over knowledge graphs. Lecture Notes in Computer Science, 571--587, Springer International Publishing, Cham, 2019.

Maribel Acosta, Amrapali Zaveri, Elena Simperl, Dimitris Kontokostas, Fabian Flöck, and Jens Lehmann. Detecting Linked Data quality issues via crowdsourcing: A DBpedia study. Semant. Web, (9)3:303--335, IOS Press, April 2018.

Melissa F Adasme, Katja L Linnemann, Sarah Naomi Bolz, Florian Kaiser, Sebastian Salentin, V Joachim Haupt, and Michael Schroeder. PLIP 2021: expanding the scope of the protein-ligand interaction profiler to DNA and RNA. Nucleic Acids Res., (49)W1:W530--W534, Oxford University Press (OUP), July 2021.

Melissa F. Adasme, Sarah Naomi Bolz, Ali Al-Fatlawi, and Michael Schroeder. Decomposing compounds enables reconstruction of interaction fingerprints for structure-based drug screening. Journal of Cheminformatics, (14)1Springer Science and Business Media LLC, March 2022. [PUMA: imported topic_lifescience] URL

Andrea Agazzi, Jianfeng Lu, and Sayan Mukherjee. Global optimality of Elman-type RNNs in the mean-field regime. In Andreas Krause, Emma Brunskill, Kyunghyun Cho, Barbara Engelhardt, Sivan Sabato, and Jonathan Scarlett (Eds.), Proceedings of the 40th International Conference on Machine Learning, (202):196--227, PMLR, 23--29 Jul 2023. [PUMA: {RNN}s, regime topic_mathfoundation Optimality, mean-field Elman-type] URL

Najia Ahmadi, Quang Vu Nguyen, Martin Sedlmayr, and Markus Wolfien. A comparative patient-level prediction study in OMOP CDM: applicative potential and insights from synthetic data. Scientific Reports, (14)1:2287, January 2024. [PUMA: topic_lifescience] URL

Najia Ahmadi, Michele Zoch, Patricia Kelbert, Richard Noll, Jannik Schaaf, Markus Wolfien, and Martin Sedlmayr. Methods used in the development of common data models for health data: Scoping review. JMIR Med. Inform., (11):e45116, August 2023. [PUMA: Observational Data Healthcare; Interoperability; health Repositories; Interoperability Partnership elements; elements Healthcare model; ; Process; Medical Informatics; data; harmonisation; Suggestive data Process record; stakeholder Standardized Repositories Outcomes Partnership; involvement common record topic_lifescience Development harmonisation model Informatics electronic]

Ahmad Ahmadov, Maik Thiele, Wolfgang Lehner, and Robert Wrembel. Context Similarity for Retrieval-Based Imputation. 1017--1024, July 2017. [PUMA: imported]

Yamen Ajjour, Pavel Braslavski, Alexander Bondarenko, and Benno Stein. Identifying argumentative questions in web search logs. Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, ACM, New York, NY, USA, July 2022. [PUMA: topic_language]

Yamen Ajjour, Henning Wachsmuth, Johannes Kiesel, Martin Potthast, Matthias Hagen, and Benno Stein. Data Acquisition for Argument Search: The args.me Corpus. KI 2019: Advances in Artificial Intelligence, 48–59, Springer International Publishing, 2019. [PUMA: imported] URL

Christopher Akiki, Maik Fröbe, Matthias Hagen, and Martin Potthast. Learning to Rank Arguments with Feature Selection. In Guglielmo Faggioli, Nicola Ferro, Alexis Joly, Maria Maistro, and Florina Piroi (Eds.), Proceedings of the Working Notes of CLEF 2021 - Conference and Labs of the Evaluation Forum, Bucharest, Romania, September 21st - to - 24th, 2021, (2936):2292--2301, CEUR-WS.org, 2021. [PUMA: imported] URL

Christopher Akiki, Lukas Gienapp, and Martin Potthast. Tracking Discourse Influence in Darknet Forums. arXiv, 2022. [PUMA: topic_language]

Christopher Akiki, Odunayo Ogundepo, Aleksandra Piktus, Xinyu Zhang, Akintunde Oladipo, Jimmy Lin, and Martin Potthast. Spacerini: Plug-and-play search engines with Pyserini and Hugging Face. arXiv, 2023. [PUMA: topic_language]

Christopher Akiki, Giada Pistilli, Margot Mieskes, Matthias Gallé, Thomas Wolf, Suzana Ilić, and Yacine Jernite. BigScience: A case study in the social construction of a multilingual large language model. arXiv, 2022. [PUMA: topic_language]

Christopher Akiki, and Martin Potthast. Exploring Argument Retrieval with Transformers. In Linda Cappellato, Carsten Eickhoff, Nicola Ferro, and Aurélie Névéol (Eds.), Working Notes of CLEF 2020 - Conference and Labs of the Evaluation Forum, Thessaloniki, Greece, September 22-25, 2020, (2696)CEUR-WS.org, 2020. [PUMA: imported] URL

Christopher Akiki, and Martin Potthast. BERTian Poetics: Constrained Composition with Masked LMs. arXiv, 2021.

Akshay Akshay, Masoud Abedi, Navid Shekarchizadeh, Fiona C Burkhard, Mitali Katoch, Alex Bigger-Allen, Rosalyn M Adam, Katia Monastyrskaya, and Ali Hashemi Gheinani. MLcps: machine learning cumulative performance score for classification problems. Gigascience, (12)December 2022. [PUMA: problems; topic_federatedlearn score unified learning; package; evaluation machine Python evaluation; model classification]

Akshay Akshay, Mitali Katoch, Masoud Abedi, Navid Shekarchizadeh, Mustafa Besic, Fiona C Burkhard, Alex Bigger-Allen, Rosalyn M Adam, Katia Monastyrskaya, and Ali Hashemi Gheinani. SpheroScan: a user-friendly deep learning tool for spheroid image analysis. Gigascience, (12)Oxford University Press (OUP), December 2022. [PUMA: image deep learning; analysis; spheroids; Image screening; Mask 3D topic_federatedlearn R-CNN; high-throughput segmentation]

Akshay Akshay, Mitali Katoch, Navid Shekarchizadeh, Masoud Abedi, Ankush Sharma, Fiona C Burkhard, Rosalyn M Adam, Katia Monastyrskaya, and Ali Hashemi Gheinani. Machine Learning Made Easy (MLme): a comprehensive toolkit for machine learning-driven data analysis. Gigascience, (13)January 2024. [PUMA: problems; topic_federatedlearn visualization learning; data machine analysis; AutoML; classification]