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
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
Towards the interpretability of deep learning models for multi-modal neuroimaging: Finding structural changes of the ageing brain. NeuroImage, (261):119504, 2022. [PUMA: Ageing, Brain-age, Cardiovascular Explainable Structural a.i., deep factors, learning mri, risk] URL
Neural machine translating from natural language to SPARQL. Future Generation Computer Systems, (117):510--519, 2021. [PUMA: Learning Machine Natural Neural SPARQL, Translation, knowledge language queries, structured] URL
Stability selection enables robust learning of differential equations from limited noisy data. Proc. Math. Phys. Eng. Sci., (478)2262:20210916, The Royal Society, Juni 2022. [PUMA: PAR differential equations; learning learning; machine proteins; regression; selection; sparse stability statistical theory]
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;]
Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology. Med. Image Anal., (79)102474:102474, Elsevier BV, Juli 2022. [PUMA: Artificial Computational Convolutional Learning; Multiple-Instance Vision Weakly-supervised deep intelligence; learning networks; neural pathology; transformers;]
Individual modelling of haematotoxicity with NARX neural networks: A knowledge transfer approach. Heliyon, (9)7:e17890, Elsevier BV, Juli 2023. [PUMA: Haematopoiesis; Precision Recurrent System Transfer identification; learning medicine; networks; neural unit_transfer]