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12.S990 Quantifying Uncertainty | Earth, Atmospheric, and Planetary Sciences

The ability to quantify the uncertainty in our models of nature is fundamental to many inference problems in Science and Engineering. In this course, we study advanced methods to represent, sample, update and propagate uncertainty. This is a "hands on" course: Methodology will be coupled with applications. The course will include lectures, invited talks, discussions, reviews and projects and will meet once a week to discuss a method and its applications.

Keywords:: Computational Modeling and Simulation, Sparse Optimization, Algorithms and Data Structures, boundary value problems, Hierarchical Bayes, Variational Bayes, Particle Filters & Smoothers, Polynomial Chaos, Systems Optimization, Dimensionality Reduction, Applied Mathematics

Disciplines:

Science and Technology / Geoscience

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More about this material

Material Type:: Online Course
Date Added to MERLOT:: May 12, 2016
Date Modified in MERLOT:: May 12, 2016
Author:: Ravela, Sai
Submitter:: Barbra Bied Sperling

Primary Audience:: College General Ed, College Lower Division, College Upper Division, Graduate School
Technical Format:: Website
Mobile Compatibility:: Not specified at this time
Language:: English
Cost Involved:: No
Source Code Available:: No
Creative Commons:: This work is licensed under a Attribution-NonCommercial-ShareAlike 3.0 United States