Automated Model Discovery
Lecture
Main Campus
Course Description
Fundamentals of physics-based modeling and deep learning; deep neural networks, recurrent neural networks, constitutive artificial neural networks; Bayesian methods; training, testing, and validation; prediction and uncertainty quantification; soft materials and living matter; discovering models, parameters, and experiments to best explain soft matter systems. Prerequisite: ME80.
ME 233
Units: 3
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Typically Offered
Not Available
Grading Basis
Letter or Credit/No Credit
Class Level
Graduate
Instructional Mode
In Person
Gen Ed Requirement(s)
None
