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cs.LG2025
Predictive Modeling and Uncertainty Quantification of Fatigue Life in Metal Alloys using Machine Learning
Jiang Chang, Deekshith Basvoju, Aleksandar Vakanski +2
Recent advancements in machine learning-based methods have demonstrated great potential for improved property prediction in material science. However, reliable estimation of the co…
cs.LG2023
Uncertainty Quantification in Multivariable Regression for Material Property Prediction with Bayesian Neural Networks
Longze Li, Jiang Chang, Aleksandar Vakanski +3
With the increased use of data-driven approaches and machine learning-based methods in material science, the importance of reliable uncertainty quantification (UQ) of the predicted…