Augmenting fatigue-life ML models with Basquin-model features and boundary losses is claimed to improve prediction and uncertainty quantification, but key equations and one results table contain errors.
Deep learning in two -dimensional materials: Characterization, prediction, and design
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Predictive Modeling and Uncertainty Quantification of Fatigue Life in Metal Alloys using Machine Learning
Augmenting fatigue-life ML models with Basquin-model features and boundary losses is claimed to improve prediction and uncertainty quantification, but key equations and one results table contain errors.