Insights into the Drivers and Spatiotemporal Trends of Extreme Mediterranean Wildfires with Statistical Deep Learning. Artificial Intelligence for the Earth Systems, (2)4American Meteorological Society, Oktober 2023. [PUMA: Deep Extreme Learning Mediterranean Spatiotemporal Statistical Trends Wildfires zno] URL
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]
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
A Light-weight and Unsupervised Method for Near Real-time Behavioral Analysis using Operational Data Measurement. The International Conference for High Performance Computing, Networking, Storage, and Analysis, Dallas, Texas, USA, Januar 2022. [PUMA: Cluster Computer Computing, Distributed, Learning Machine Parallel, Science and myOwn] URL
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
Explainable Earth Surface Forecasting under Extreme Events. arXiv, 2024. [PUMA: (cs.LG), Computer FOS: Learning Machine and information sciences sciences, topic_earthenvironment] URL
Assessing the Impact of Image Dataset Features on Privacy-Preserving Machine Learning. arXiv preprint arXiv:2409.01329, arXiv, September 2024. [PUMA: area_responsibleai area_bigdata (cs.CR), (cs.CV), (cs.LG), Computer Cryptography FOS: Learning Machine Pattern Recognition Security Vision and ep information sciences]
Deep reinforcement learning with artificial microswimmers. Emerging Topics in Artificial Intelligence (ETAI) 2022, (12204):104--110, 2022. [PUMA: topic_physchemistry Deep artificial learning microswimmers reinforcement]
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: topic_neuroinspired Disease Feature Graph-Based Impact Investigating Neuroimaging Prediction Selection learning]
Steuerung von Compliant-Mechanismen durch Reinforcement Learning. GETRIEBETAGUNG 2022, 121, 2022. [PUMA: topic_engineering Compliant-Mechanismen Learning Reinforcement Steuerung]
Self-organized free-flight arrival for urban air mobility. Transportation Research Part C: Emerging Technologies, (167):104806, 2024. [PUMA: topic_engineering Deep Urban air eVTOL learning mobility reinforcement] URL
Enhanced method for reinforcement learning based dynamic obstacle avoidance by assessment of collision risk. Neurocomputing, (568):127097, 2024. [PUMA: topic_engineering Collision Dynamic Reinforcement Training avoidance environment learning metric obstacle risk] URL
Neural network-assisted humanisation of COVID-19 hamster transcriptomic data reveals matching severity states in human disease. eBioMedicine, (108):105312, 2024. [PUMA: topic_mathfoundation COVID-19, Cross-species Deep Disease Hamster RNA-seq, Single-cell analysis, learning matching, model, state] URL
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
PredicTF: prediction of bacterial transcription factors in complex microbial communities using deep learning. Environmental Microbiome, (17)Dezember 2022. [PUMA: PredicTF: Zno bacterial complex learning microbialdeep prediction transcription]
Towards the interpretability of deep learning models for multi-modal neuroimaging: Finding structural changes of the ageing brain. NeuroImage, (261):119504, 2022. [PUMA: topic_neuroinspired topic_lifescience Ageing, Brain-age, Cardiovascular Explainable Structural a.i., deep factors, learning mri, risk] URL
Sampling Bias Due to Near-Duplicates in Learning to Rank. Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, 1997–2000, Association for Computing Machinery, New York, NY, USA, 2020. [PUMA: bias learning near-duplicate-detection, novelty principle, rank, selection to] URL
Wie bereit sind Studierende für die Nutzung von KI-Technologien? Eine Annäherung an die KI-Readiness Studierender im Kontext des Projektes "tech4comp". Waxmann : Münster ; New York, 2021. [PUMA: (Learning 370 Activities), Artificial Assessment, Bewertung, Bildungswesen, Deployment Digitale Education, Empirical Empirische Erziehung, Forschung, Higher Hochschule, Hochschullehre, Human Intelligenz, Judgement, Judgment, K\"{u}nstliche Learning Lernprozess, Male Medien, Medieneinsatz, Mediennutzung, Mensch, Nachteil, Project, Projects Projekt, Qualitative Schul- Student, Technologie, Technology, University Untersuchung, Use Utilisation Utilization Vergleich, Vorteil, being, education institute, intelligence, lecturing, media, of process, research student, study, teaching, und] URL
Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology. Med. Image Anal., (79)102474:102474, Elsevier BV, Juli 2022. [PUMA: topic_lifescience Artificial Computational Convolutional Learning; Multiple-Instance Vision Weakly-supervised deep intelligence; learning networks; neural pathology; transformers;]
Common features in lncRNA annotation and classification: A survey. Noncoding RNA, (7)4:77, MDPI AG, Dezember 2021. [PUMA: classification coding extraction; feature learning lncRNA; machine problems; sequence;]