Publications

Markus Bauer, and Christoph Augenstein. Self-supervised learning in histopathology: New perspectives for prostate cancer grading. Lecture Notes in Computer Science, 348--360, Springer Nature Switzerland, Cham, 2024. [PUMA: Yaff cancer grading histopathology learning prostate self-supervised topic_lifescience]

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):giad108, December 2023. [PUMA: MLcps Xack Yaff cumulative learning machine performance] URL

Meysam Alishahi, Anna Little, and Jeff M. Phillips. Linear Distance Metric Learning with Noisy Labels. Journal of Machine Learning Research, (25)121:1--53, 2024. [PUMA: Distance Learning Linear Metric Noisy_Labels Yaff imported] URL

Aruscha Kramm, Eric Peukert, André Ludwig, and Bogdan Franczyk. Machine Learning Based Mobile Capacity Estimation for Roadside Parking. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, (10):99--106, Copernicus GmbH, 2024. [PUMA: Based Capacity Estimation Learning Machine Mobile Parking Roadside yaff]

Maria Carolina Novitasari, Johannes Quaas, and Miguel R. D. Rodrigues. Cloudy with a chance of precision: satellite’s autoconversion rates forecasting powered by machine learning. Environmental Data Science, (3)Cambridge University Press (CUP), 2024. [PUMA: autoconversion forecasting learning machine rates satellite yaff] URL

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 yaff] URL

Lucas Lange, Maurice-Maximilian Heykeroth, and Erhard Rahm. Assessing the Impact of Image Dataset Features on Privacy-Preserving Machine Learning. arXiv preprint arXiv:2409.01329, arXiv, September 2024. [PUMA: (cs.CR), (cs.CV), (cs.LG), Computer Cryptography FOS: Learning Machine Pattern Recognition Security Vision and area_bigdata area_responsibleai ep information sciences xack yaff]

Dimitra Kiakou, Adam Adamopoulos, and Nico Scherf. Graph-Based Disease Prediction in Neuroimaging: Investigating the Impact of Feature Selection. Worldwide Congress on “Genetics, Geriatrics and Neurodegenerative Diseases Research", 223--230, 2022. [PUMA: Disease Feature Graph-Based Impact Investigating Neuroimaging Prediction Selection learning topic_neuroinspired yaff]

Martin Waltz, Ostap Okhrin, and Michael Schultz. Self-organized free-flight arrival for urban air mobility. Transportation Research Part C: Emerging Technologies, (167):104806, 2024. [PUMA: Deep Urban air eVTOL learning mobility reinforcement topic_engineering yaff] URL

Vincent D. Friedrich, Peter Pennitz, Emanuel Wyler, Julia M. Adler, Dylan Postmus, Kristina Müller, Luiz Gustavo Teixeira Alves, Julia Prigann, Fabian Pott, Daria Vladimirova, Thomas Hoefler, Cengiz Goekeri, Markus Landthaler, Christine Goffinet, Antoine-Emmanuel Saliba, Markus Scholz, Martin Witzenrath, Jakob Trimpert, Holger Kirsten, and Geraldine Nouailles. Neural network-assisted humanisation of COVID-19 hamster transcriptomic data reveals matching severity states in human disease. eBioMedicine, (108):105312, 2024. [PUMA: COVID-19, Cross-species Deep Disease Hamster RNA-seq, Single-cell analysis, learning matching, model, state topic_mathfoundation xack yaff] URL