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1 |
A Machine Learning and Explainable AI Framework Tailored for Unbalanced Experimental Catalyst Discovery
Semnani, Parastoo. - Berlin : Technische Universität Berlin, 2025
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2 |
A machine learning-based framework and open-source software for non intrusive water monitoring
Gross, Marie-Philine. - Berlin : Technische Universität Berlin, 2025
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3 |
A systematic review of machine learning-based prognostic models for acute pancreatitis: towards improving methods and reporting quality
Critelli, Brian. - Aachen : Universitätsbibliothek der RWTH Aachen, 2025
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4 |
Application of machine learning in predicting quality parameters in Metal Material Extrusion (MEX/M)
Asami, Mohammad Karim. - Hamburg : Technische Universität Hamburg. Universitätsbibliothek, 2025
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Artificial intelligence and machine learning
Kühl, Niklas. - Darmstadt : Universitäts- und Landesbibliothek, 2025
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6 |
Automated model discovery for tensional homeostasis: Constitutive machine learning in growth and remodeling
Holthusen, Hagen. - Hamburg : Technische Universität Hamburg. Universitätsbibliothek, 2025
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Automated model discovery for tensional homeostasis: Constitutive machine learning in growth and remodeling
Holthusen, Hagen. - Aachen : Universitätsbibliothek der RWTH Aachen, 2025
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8 |
Choosing explanation over performance: insights from machine learning-based prediction of human intelligence from brain connectivity
Thiele, Jonas A.. - Würzburg : Universität Würzburg, 2025
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9 |
Concept of a plug-and-play, machine learning digital twin of the production resource for detailed capacity planning and scheduling
Luber, Mario. - Augsburg : Universität Augsburg, 2025
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10 |
Crash testing machine learning force fields for molecules, materials, and interfaces: model analysis in the TEA Challenge 2023†
Poltavsky, Igor. - Erlangen : Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 2025
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