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, October 2023. [PUMA: Deep Extreme Learning Mediterranean Spatiotemporal Statistical Trends Wildfires] 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]
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] 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.] URL
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
Stability selection enables robust learning of differential equations from limited noisy data. Proceedings of the Royal Society of London : Series A, Mathematical, physical and engineering sciences, (478)2262Royal Society Publishing, June 2022. [PUMA: topic_lifescience FIS_scads PAR differential equations, learning learning, machine proteins, regression, selection, sparse stability statistical theory]
RTASS: a RunTime Adaptable and Scalable System for Network-on-Chip-Based Architectures. 2023 26th Euromicro Conference on Digital System Design (DSD), 585--592, IEEE, Sep 8, 2023. [PUMA: topic_federatedlearn Computer Embedded FIS_scads Machine Runtime, Scalability, Shape algorithms, architecture, computing, learning vision,] URL
Two-step dynamic obstacle avoidance. Knowledge-based systems, (302)Elsevier Science B.V., Oct 25, 2024. [PUMA: topic_engineering Deep Dynamic FIS_scads Local Supervised avoidance, learning learning, obstacle path planning, reinforcement]
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
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, July 2022. [PUMA: topic_lifescience Artificial Computational Convolutional Learning; Multiple-Instance Vision Weakly-supervised deep intelligence; learning networks; neural pathology; transformers;]