Publications

Parvaneh Joharinad, and Jürgen Jost. Mathematical principles of topological and geometric data analysis. Springer International Publishing, Cham, 2023. [PUMA: Mathematical analysis data geometric nopdf topological]

Oliver Kirsten, Martin Bogdan, and Sophie Adama. Evaluating the DoC-Forest tool for Classifying the State of Consciousness in a Completely Locked-In Syndrome Patient. 2023 7th International Conference on Imaging, Signal Processing and Communications (ICISPC), 37-41, 2023. [PUMA: Complexity Computational Consciousness Information Learning Locked-In Machine Measures Modeling Neuroscience Prediction Predictive Processing Signal Syndrome Theory Training Zno algorithms and data learning modeling models processing]

Maja Schneider. Distributed, Privacy-Aware Location Data Aggregation. 2024. [PUMA: Aggregation Data Distributed Location Privacy-Aware Xack] URL

Ekaterina Borisova, Raia Abu Ahmad, Georg Rehm, Ricardo Usbeck, Jennifer D’Souza, Markus Stocker, Sören Auer, Judith Gilsbach, Anastasia Wolschewski, Johannes Keller, Daniel Schneider, Thomas Neumuth, and Sonja Schimmler. NFDI4DS Transfer and Application. Gesellschaft für Informatik e.V., 2023. [PUMA: Artificial Data Infrastructures Intelligence NFDI NFDI4DS Research Science Zno] URL

Sonja Schimmler, Bianca Wentzel, Arnim Bleier, Stefan Dietze, Saurav Karmakar, Peter Mutschke, Angelie Kraft, Tilahun A. Taffa, Ricardo Usbeck, Zeyd Boukhers, Sören Auer, Leyla J. Castro, Marcel R. Ackermann, Thomas Neumuth, Daniel Schneider, Ziawasch Abedjan, Atif Latif, Fidan Limani, Raia Abu Ahmad, Georg Rehm, Sima Attar Khorasani, and Matthias Lieber. NFDI4DS Infrastructure and Services. Gesellschaft für Informatik e.V., 2023. [PUMA: Data Infrastructures NFDI NFDI4DS Research Zno] URL

Aris Marcolongo, Mykhailo Vladymyrov, Sebastian Lienert, Nadav Peleg, Sigve Haug, and Jakob Zscheischler. Predicting years with extremely low gross primary production from daily weather data using Convolutional Neural Networks. Environmental Data Science, (1):e2, 2022. [PUMA: Convolutional Networks Neural Predicting data gross low primary production weather]

Markus Bauer, and Christoph Augenstein. Can Unlabelled Data Improve AI Applications? A Comparative Study on Self-Supervised Learning in Computer Vision.. Proceedings of the 18th Conference on Computer Science and Intelligence Systems, (35):93–101, IEEE, September 2023. [PUMA: Comparative Computer Data Learning Self-Supervised Study Unlabelled Vision.] URL

Kristian Schultz, Saptarshi Bej, Waldemar Hahn, Markus Wolfien, Prashant Srivastava, and Olaf Wolkenhauer. ConvGeN: A convex space learning approach for deep-generative oversampling and imbalanced classification of small tabular datasets. Pattern Recognition, (147):110138, 2024. [PUMA: Convex GAN Imbalanced LoRAS Tabular data learning space] URL

Marzan Tasnim Oyshi, Sebastian Vogt, and Stefan Gumhold. TmoTA: Simple, Highly Responsive Tool for Multiple Object Tracking Annotation. In Albrecht Schmidt, Kaisa Väänänen, EditoTesh Goyal, Per Ola Kristensson, Anicia Peters, Stefanie Mueller, Julie R. Williamson, and Max L. Wilson (Eds.), CHI 2023 - Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, Association for Computing Machinery, Apr 19, 2023. [PUMA: topic_visualcomputing FIS_scads data labeling labeling, manual sequence video] URL

Weizhou Luo, Zhongyuan Yu, Rufat Rzayev, Marc Satkowski, Stefan Gumhold, Matthew McGinity, and Raimund Dachselt. PEARL: Physical Environment based Augmented Reality Lenses for In-Situ Human Movement Analysis. CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, Apr 19, 2023. [PUMA: topic_visualcomputing Analytics, FIS_scads Immersive In-situ affordance, analysis, augmented/mixed data movement physical reality, referents, visualization]

Joel Jonsson, Bevan L. Cheeseman, Suryanarayana Maddu, Krzysztof Gonciarz, and Ivo F. Sbalzarini. Parallel Discrete Convolutions on Adaptive Particle Representations of Images. IEEE Transactions on Image Processing, (31):4197--4212, Wiley-IEEE Press, Jan 1, 2022. [PUMA: topic_lifescience Convolution, Data FIS_scads Image Microscopy, Signal processing, reconstruction, resolution resolution, structures,]

Johannes Gerritzen, Andreas Hornig, and Maik Gude. Graph based process models as basis for efficient data driven surrogates - Expediting the material development process. engrXiv : engineering archive, Open Engineering Inc., Nov 16, 2024. [PUMA: topic_engineering Data FIS_scads Process Surrogate decision development, driven making modeling,]

Elena Williams, Manuel Kienast, Evelyn Medawar, Janis Reinelt, Alberto Merola, Sophie Anne Ines Klopfenstein, Anne Rike Flint, Patrick Heeren, Akira-Sebastian Poncette, Felix Balzer, Nico Scherf, and others. A standardized clinical data harmonization pipeline for scalable ai application deployment (fhir-dhp): Validation and usability study. JMIR Medical Informatics, (11):e43847, JMIR Publications Toronto, Canada, 2023. [PUMA: topic_neuroinspired (fhir-dhp) ai application clinical data deployment harmonization pipeline scalable standardized]

Johannes Gerritzen, Andreas Hornig, Benjamin Gröger, and Maik Gude. A Data Driven Modelling Approach for the Strain Rate Dependent 3D Shear Deformation and Failure of Thermoplastic Fibre Reinforced Composites: Experimental Characterisation and Deriving Modelling Parameters. Journal of Composites Science, (6)10:318, MDPI, 2022. [PUMA: topic_engineering 3D Approach Characterisation Composites Data Deformation Dependent Driven Experimental Failure Fibre Modelling Rate Reinforced Shear Strain Thermoplastic]

Patrick Ebel, Pavlo Bazilinskyy, Angel Hsing-Chi Hwang, Wendy Ju, Hauke Sandhaus, Aravinda Ramakrishnan Srinivasan, Qian Yang, and Philipp Wintersberger. Breaking Barriers: Workshop on Open Data Practices in AutoUI Research. Adjunct Proceedings of the 15th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, 227--230, 2023. [PUMA: topic_visualcomputing AutoUI Data Open Practices Research Workshop]

Patrick Ebel, Kim Julian Gülle, Christoph Lingenfelder, and Andreas Vogelsang. Exploring Millions of User Interactions with ICEBOAT: Big Data Analytics for Automotive User Interfaces. Proceedings of the 15th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, 81--92, 2023. [PUMA: topic_visualcomputing Analytics Automotive Big Data ICEBOAT Interactions Interfaces User]

Patrick Ebel, Ibrahim Emre Göl, Christoph Lingenfelder, and Andreas Vogelsang. Destination Prediction Based on Partial Trajectory Data. 2020. [PUMA: Based Data Destination Partial Prediction Trajectory on] URL

Patrick Ebel, Kim Julian Gülle, Christoph Lingenfelder, and Andreas Vogelsang. ICEBOAT: An Interactive User Behavior Analysis Tool for Automotive User Interfaces. Adjunct Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology, Association for Computing Machinery, New York, NY, USA, 2022. [PUMA: topic_visualcomputing Data Design Driving Human-Computer In-Vehicle Information Interaction Naturalistic System Tools Visualization] URL

Suryanarayana Maddu, Bevan L. Cheeseman, Ivo F. Sbalzarini, and Christian L. Müller. Stability selection enables robust learning of partial differential equations from limited noisy data. arXiv, 2019. [PUMA: (cs.LG), (math.NA), (physics.data-an), Analysis Analysis, Computer Data FOS: Learning Machine Mathematics, Numerical Physical Probability Statistics and information sciences sciences,] URL

André Petermann, Martin Junghanns, Stephan Kemper, Kevin Gómez, Niklas Teichmann, and Erhard Rahm. Graph Mining for Complex Data Analytics. 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW), 1316--1319, December 2016. [PUMA: Data Intelligence Mining;Business algorithms;Conferences;Graph analysis;Data and design mining;Business;Algorithm models;Libraries;Partitioning]