Katalog der Deutschen Nationalbibliothek

Ergebnis der Suche nach: "Machine Learning"
im Bestand: Gesamter Bestand

43541 - 43550 von 43748

	43541	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
	43542	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
	43543	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
	43544	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
	43545	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
	43546	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
	43547	Vegetation detection using vegetation indices algorithm supported by statistical machine learning Enthalten in Environmental monitoring and assessment Bd. 194, 24.9.2022, Nr. 11, date:11.2022: 1-12
	43548	Vehicle performance enhancement through magnetorheological dampers and machine learning integration Enthalten in Discover applied sciences Bd. 7, 16.10.2025, Nr. 11, date:11.2025: 1-39
	43549	Vehicle-specific power-based emission modeling using unsupervised machine learning techniques Enthalten in Environmental science and pollution research Bd. 32, 23.6.2025, Nr. 27, date:6.2025: 16120-16141
	43550	Ventricular geometry–regularized QRSd predicts cardiac resynchronization therapy response: machine learning from crosstalk between electrocardiography and echocardiography Enthalten in The international journal of cardiovascular imaging Bd. 35, 18.5.2019, Nr. 7, date:7.2019: 1221-1229

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