Katalog der Deutschen Nationalbibliothek

Ergebnis der Suche nach: "Machine Learning"
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16191 - 16200 von 16533

	16191	Understanding Learning from EEG Data: Combining Machine Learning and Feature Engineering Based on Hidden Markov Models and Mixed Models Enthalten in Neuroinformatics Bd. 22, 10.9.2024, Nr. 4, date:10.2024: 487-497
	16192	Understanding machine learning applications in dementia research and clinical practice: a review for biomedical scientists and clinicians Enthalten in Alzheimer's research & therapy Bd. 16, 1.8.2024, Nr. 1, date:12.2024: 1-21
	16193	Understanding phase transitions of α-quartz under dynamic compression conditions by machine-learning driven atomistic simulations Enthalten in npj computational materials Bd. 11, 2.3.2025, Nr. 1, date:12.2025: 1-9
	16194	Understanding predictions of drug profiles using explainable machine learning models Enthalten in BioData Mining Bd. 17, 1.8.2024, Nr. 1, date:12.2024: 1-25
	16195	Understanding quality of analytics trade-offs in an end-to-end machine learning-based classification system for building information modeling Enthalten in Journal of Big Data Bd. 8, 15.2.2021, Nr. 1, date:12.2021: 1-30
	16196	Understanding quantum machine learning also requires rethinking generalization Enthalten in Nature Communications Bd. 15, 13.3.2024, Nr. 1, date:12.2024: 1-12
	16197	Understanding the importance of key risk factors in predicting chronic bronchitic symptoms using a machine learning approach Enthalten in BMC medical research methodology Bd. 19, 29.3.2019, Nr. 1, date:12.2019: 1-12
	16198	Understanding the social determinants of child mortality in Latin America over the last two decades: a machine learning approach Enthalten in Scientific reports Bd. 13, 27.11.2023, Nr. 1, date:12.2023: 1-8
	16199	Understanding the spread of agriculture in the Western Mediterranean (6th-3rd millennia BC) with Machine Learning tools Enthalten in Nature Communications Bd. 16, 15.1.2025, Nr. 1, date:12.2025: 1-18
	16200	UNDERSTANDING USER EQUILIBRIUM STATES OF ROAD NETWORKS USING BIG TRAJECTORY DATA Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLVIII-1/W2-2023, 2023: 331-337. 7 S.