Publications

Tom Richard Vargis, and Siavash Ghiasvand. Content-Aware Depth-Adaptive Image Restoration. Proceedings of the 29th International Conference on Automation and Computing, Sunderland, UK, January 2024. [PUMA: Computer Learning, Machine Pattern Recognition, Science Vision and myOwn] 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)1Nature Publishing Group, Jan 27, 2024. [PUMA: Databases, Electronic FIS_scads Factual, Health Humans, Informatics, Learning, Machine Medical Records topic_lifescience yaff]

Johannes Gerritzen, Andreas Hornig, Peter Winkler, and Maik Gude. Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning. ECCM21 - Proceedings of the 21st European Conference on Composite Materials, (3):1252--1259, European Society for Composite Materials (ESCM), Jul 2, 2024. [PUMA: Convolutional Direct FIS_scads Fiber Machine Strain area_architectures dependency, identification, learning, networks, neural parameter plastics rate reinforced topic_engineering yaff] URL

Frank Cichos, Santiago Mui�os Landin, and Ravi Pradip. Chapter 5 - Artificial intelligence (AI) enhanced nanomotors and active matter. In Yuebing Zheng, and Zilong Wu (Eds.), Intelligent Nanotechnology, 113--144, Elsevier, 2023. [PUMA: topic_physchemistry Active Feedback Machine Multi Optical Reinforcement agent control control, learning, particles, reinforcement] URL

Veronia Iskandar, Mohamed A. Abd El Ghany, and Diana Goehringer. NDP-RANK: Prediction and ranking of NDP systems performance using machine learning. Microprocessors and Microsystems, (96):104707, 2023. [PUMA: topic_federatedlearn Design Machine Modeling, Near-data Prediction, exploration learning, processing, space] URL

Mersedeh Sadeghi, Daniel Pöttgen, Patrick Ebel, and Andreas Vogelsang. Explaining the Unexplainable: The Impact of Misleading Explanations on Trust in Unreliable Predictions for Hardly Assessable Tasks. Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization, 36–46, Association for Computing Machinery, New York, NY, USA, 2024. [PUMA: topic_visualcomputing XAI, explainability, learning, machine trust] URL