CME 262: Imaging with Incomplete Information (CEE 260G, GEOPHYS 260G)

Computational & Mathematical Engineering Stanford University 4.0 credits

Course Description

Statistical and computational methods for inferring images from incomplete data. Bayesian inference methods are used to combine data and quantify uncertainty in the estimate. Fast linear algebra tools are used to solve problems with many pixels and many observations. Applications from several fields but mainly in earth sciences. Prerequisites: Linear algebra and probability theory.

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