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Bayesian-Optimized Physics-Informed Deep Autoencoders for Efficient Calibration of Geotechnical Constitutive Models: A NorSand Case Study
Publisher: American Society of Civil Engineers
Abstract: AbstractRecent advancements in deep learning have revolutionized constitutive model calibration
in geotechnical engineering by automatically identifying complex patterns in high-dimensional
data, enhancing accuracy, and ...
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