Katalog der Deutschen Nationalbibliothek

Ergebnis der Suche nach: "Machine Learning"
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43501 - 43510 von 43711

	43501	Variability analysis of soil organic carbon content across land use types and its digital mapping using machine learning and deep learning algorithms Enthalten in Environmental monitoring and assessment Bd. 197, 10.4.2025, Nr. 5, date:5.2025: 1-32
	43502	Variable resolution machine learning optimization of antennas using global sensitivity analysis Enthalten in Scientific reports Bd. 14, 13.11.2024, Nr. 1, date:12.2024: 1-23
	43503	Variable selection in social-environmental data: sparse regression and tree ensemble machine learning approaches Enthalten in BMC medical research methodology Bd. 20, 10.12.2020, Nr. 1, date:12.2020: 1-10
	43504	Variant-driven early warning via unsupervised machine learning analysis of spike protein mutations for COVID-19 Enthalten in Scientific reports Bd. 12, 3.6.2022, Nr. 1, date:12.2022: 1-14
	43505	Variational autoencoder-based techniques for a streamlined cross-topology modeling and optimization workflow in electrical drives Enthalten in Autonomous intelligent systems Bd. 4, 24.5.2024, Nr. 1, date:12.2024: 1-10
	43506	Variational Bayes machine learning for risk adjustment of general outcome indicators with examples in urology Enthalten in npj digital medicine Bd. 7, 14.9.2024, Nr. 1, date:12.2024: 1-11
	43507	Variational Monte Carlo—bridging concepts of machine learning and high-dimensional partial differential equations Enthalten in Advances in computational mathematics Bd. 45, 5.10.2019, Nr. 5-6, date:12.2019: 2503-2532
	43508	Various optimized machine learning techniques to predict agricultural commodity prices Enthalten in Neural computing & applications Bd. 36, 16.4.2024, Nr. 19, date:7.2024: 11439-11459
	43509	Vascular-related biological stress, DNA methylation, allostatic load and domain-specific cognition: an integrated machine learning and causal inference approach Enthalten in BMC neurology Bd. 25, 23.4.2025, Nr. 1, date:12.2025: 1-9
	43510	VaxOptiML: leveraging machine learning for accurate prediction of MHC-I and II epitopes for optimized cancer immunotherapy Enthalten in Immunogenetics Bd. 77, 7.12.2024, Nr. 1, date:12.2025: 1-15

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