GEN 2329
Imaging with Incomplete Information
Stanford University · UGRD · Fall 2026
1 section
Catalog 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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Availability not recently verifiedClass #stanford-2329Fall 2026UGRD3 credits
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