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26541 |
Quantitative Gaussian approximation of randomly initialized deep neural networks
Enthalten in Machine learning Bd. 113, 25.6.2024, Nr. 9, date:9.2024: 6373-6393
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26542 |
Quantitative prediction of disinfectant tolerance in Listeria monocytogenes using whole genome sequencing and machine learning
Enthalten in Scientific reports Bd. 15, 26.3.2025, Nr. 1, date:12.2025: 1-11
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26543 |
Quantitative texture analysis using machine learning for predicting interpretable pulmonary perfusion from non-contrast computed tomography in pulmonary embolism patients
Enthalten in Respiratory research Bd. 25, 28.10.2024, Nr. 1, date:12.2024: 1-15
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26544 |
Quantitative three-dimensional imaging of chemical short-range order via machine learning enhanced atom probe tomography
Enthalten in Nature Communications Bd. 14, 16.11.2023, Nr. 1, date:12.2023: 1-11
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26545 |
Quantized hashing: enabling resource-efficient deep learning models at the edge
Enthalten in International journal of information technology Bd. 16, 16.3.2024, Nr. 4, date:4.2024: 2353-2361
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26546 |
Quantized Salp Swarm Algorithm (QSSA) for optimal feature selection
Enthalten in International journal of information technology Bd. 15, 7.2.2023, Nr. 2, date:2.2023: 725-734
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26547 |
Quantum-accurate machine learning potentials for metal-organic frameworks using temperature driven active learning
Enthalten in npj computational materials Bd. 10, 8.10.2024, Nr. 1, date:12.2024: 1-13
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26548 |
Quantum Advantage Seeker with Kernels (QuASK): a software framework to speed up the research in quantum machine learning
Enthalten in Quantum machine intelligence Bd. 5, 2.5.2023, Nr. 1, date:6.2023: 1-11
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26549 |
Quantum and classical machine learning for the classification of non-small-cell lung cancer patients
Enthalten in SN applied sciences Bd. 2, 16.5.2020, Nr. 6, date:6.2020: 1-10
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26550 |
Quantum and classical machine learning investigation of synthesis–structure relationships in epitaxially grown wide band gap semiconductors
Enthalten in Materials Research Society: MRS communications Bd. 14, 9.7.2024, Nr. 4, date:8.2024: 660-666
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