66 citations · 66 across the 2 of their papers we have counts for
2 papers
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★ 66 cited
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…