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Searched for: 1 subject found.
2.C51 Physical Systems Modeling and Design Using Machine Learning
(
); second half of term
(Subject meets with 2.C01)
Prereq: 6.C51 and (18.0751 or 18.0851)
Units: 1-3-2
Begins Mar 31. Lecture: F11-1 (3-270)
Building on core material in 6.C51, encourages open-ended exploration of the increasingly topical intersection between artificial intelligence and the physical sciences. Uses energy and information, and their respective optimality conditions, to define supervised and unsupervised learning algorithms as well as ordinary and partial differential equations. Subsequently, physical systems with complex constitutive relationships are drawn from elasticity, biophysics, fluid mechanics, hydrodynamics, acoustics, and electromagnetics to illustrate how machine learning-inspired optimization can approximate solutions to forward and inverse problems in these domains. Students taking graduate version complete additional assignments. Students cannot receive credit without completion of the core subject 6.C51.
G. Barbastathis
No textbook information available
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