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
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
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
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]
A methodology for direct parameter identification for experimental results using machine learning — Real world application to the highly non-linear deformation behavior of FRP. Computational Materials Science, (244 (2024))Elsevier Science B.V., September 2024. [PUMA: area_architectures topic_engineering Constitutive FIS_scads Fiber Machine Neural Parameter identification learning, modeling, networks, plastics, reinforced]
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: area_architectures topic_engineering Convolutional Direct FIS_scads Fiber Machine Strain dependency, identification, learning, networks, neural parameter plastics rate reinforced] URL
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]
Towards Standardizing Ophthalmic Data for Seamless Interoperability in Eye Care. Studies in health technology and informatics, (317):139--145, IOS Press, Amsterdam u. a., Aug 30, 2024. [PUMA: topic_lifescience Diseases/therapy, Electronic Eye FIS_scads Germany, Health Humans, Information Interoperability/standards, Learning, Level Machine Ophthalmology Records/standards, Seven/standards,]
CCR2 macrophage response determines the functional outcome following cardiomyocyte transplantation. Genome medicine, (15)1BioMed Central, London, Aug 10, 2023. [PUMA: topic_lifescience Animals, C57BL, Cardiac/metabolism, Cell FIS_scads Immunocompromised, Inbred Infarction, Machine Macrophages, Macrophages/metabolism, Mice, Monocytes/metabolism Myocardial Myocytes, Single-cell, infarction, learning, therapy,]
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
Data-driven determination of plant growth stages for improved weather index insurance design. Agricultural Finance Review, Emerald Group Publishing, Bingley, 2024. [PUMA: topic_engineering FIS_scads Generalized Machine Plant Temporal Weather additive basis growth index insurance learning, model, risk, stages,]
Identifying Secondary School Students' Misconceptions about Machine Learning: An Interview Study. WiPSCE '24: Proceedings of the 19th WiPSCE Conference on Primary and Secondary Computing Education Research, 1--10, Association for Computing Machinery, Sep 16, 2024. [PUMA: area_responsibleai FIS_scads artificial conceptions intelligence, interview learning, machine mental misconceptions, models, qualitative research, students study,]
Brief Summary of Existing Research on Students’ Conceptions of AI. 1--2, October 2022. [PUMA: area_responsibleai FIS_scads artificial beliefs, conceptions, education, ideas, intelligence, k-12 learning, machine mental models, preconceptions]
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
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]
Evaluating the DoC-Forest tool for Classifying the State of Consciousness in a Completely Locked-In Syndrome Patient. 2023 7th International Conference on Imaging, Signal Processing and Communications (ICISPC), 37-41, 2023. [PUMA: Complexity Computational Consciousness Information Learning Locked-In Machine Measures Modeling Neuroscience Prediction Predictive Processing Signal Syndrome Theory Training Zno algorithms and data learning modeling models processing]
Extendable hybrid approach to detect conscious states in a CLIS patient using machine learning. SNE Simul. Notes Eur., (32)1:37--45, ARGESIM Arbeitsgemeinschaft Simulation News, 2022. [PUMA: Zno conscious hybrid learning machine patient states {CLIS}]
Cost-Sensitive Best Subset Selection for Logistic Regression: A Mixed-Integer Conic Optimization Perspective. KI 2023: Advances in Artificial Intelligence: 46th German Conference on AI, Berlin, Germany, September 26--29, 2023, Proceedings, 114--129, Springer-Verlag, Berlin, Heidelberg, 2023. [PUMA: Zno best conic cost-sensitive interpretable learning machine meta-learning mixed-integer optimization selection subset]
MLcps: machine learning cumulative performance score for classification problems. GigaScience, (12):giad108, December 2023. [PUMA: MLcps Xack Yaff cumulative learning machine performance] URL