ME 233
Automated Model Discovery
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.
Sources
- Course catalogue ↗2026-2027