Data-Driven Dynamical Systems


AMATH 568 - Advanced Methods for Ordinary Differential Equations


Below are key pieces of information for the course (WINTER 2020).





AMATH 563 - Inferring Structure of Complex Systems


Spring Quarters


Introduces fundamental concepts of network science and graph theory for complex dynamical systems. Merges concepts from model selection, information theory, statistical inference, neural networks, deep learning and machine learning for building reduced order models of dynamical systems using sparse sampling of high-dimensional data.



AMATH 482/582 - Computational Methods for Data Analysis


Winter Quarters


Exploratory and objective data analysis methods applied to the physical, engineering and biological sciences. Brief overview of statistical methods and their computational implementation for time series analysis, spectral analysis, filtering methods, principal component analysis, proper orthogonal decompositions, and image processing and compression.



Reduced Order Modeling [View]


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This website makes available all lectures for a new course that is still in development on Reduced Order Modeling. The course covers topics in nonlinear model reduction, balanced truncation and reduced basis methods.



AMATH 301 - Beginning Scientific Computing [View]


All Quarters


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This website makes available all lectures for AMATH 301, Beginning Scientific Computing. This course provides an introduction to programming and the MATLAB scripting language. It is intended for engineering and physical sciences majors, providing a broad introduction to the power of numerical methods, scientific computing and MATLAB programming.
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