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Ergebnis der Suche nach: "Machine Learning"
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15761 - 15770 von 16454
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Artikel 15761 Synergizing physics and machine learning for advanced battery management
Enthalten in Communications engineering Bd. 3, 17.9.2024, Nr. 1, date:12.2024: 1-9
Online Ressource
Artikel 15762 Synergizing quantum techniques with machine learning for advancing drug discovery challenge
Enthalten in Scientific reports Bd. 14, 28.12.2024, Nr. 1, date:12.2024: 1-12
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Artikel 15763 Synthesis of computer simulation and machine learning for achieving the best material properties of filled rubber
Enthalten in Scientific reports Bd. 10, 22.10.2020, Nr. 1, date:12.2020: 1-11
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Artikel 15764 Synthesis optimization and adsorption modeling of biochar for pollutant removal via machine learning
Enthalten in Biochar Bd. 5, 23.4.2023, Nr. 1, date:12.2023: 1-25
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Artikel 15765 Synthesizing explainable counterfactual policies for algorithmic recourse with program synthesis
Enthalten in Machine learning Bd. 112, 2.2.2023, Nr. 4, date:4.2023: 1389-1409
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Artikel 15766 SYNTHETIC DATA GENERATION AND TESTING FOR THE SEMANTIC SEGMENTATION OF HERITAGE BUILDINGS
Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLVIII-M-2-2023, 2023: 1189-1196. 8 S.
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Artikel 15767 Synthetic seed production in Crataegus monogyna L. and prediction of regeneration of synthetic seeds with machine learning algorithms
Enthalten in Plant cell, tissue and organ culture Bd. 161, 8.4.2025, Nr. 1, date:4.2025: 1-13
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Artikel 15768 SyntheVAEiser: augmenting traditional machine learning methods with VAE-based gene expression sample generation for improved cancer subtype predictions
Enthalten in Genome biology Bd. 25, 18.12.2024, Nr. 1, date:12.2024: 1-18
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Artikel 15769 Systematic evaluation of generative machine learning capability to simulate distributions of observables at the large hadron collider
Enthalten in The European physical journal / C / Particles and fields Bd. 84, 9.9.2024, Nr. 9, date:9.2024: 1-31
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Artikel 15770 Systematic evaluation of supervised machine learning for sample origin prediction using metagenomic sequencing data
Enthalten in Biology direct Bd. 15, 10.12.2020, Nr. 1, date:12.2020: 1-12
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