[Eoas-seminar] GFDI Colloquium on Monday, APRIL 22, at 11:00AM in Melvin Stern Seminar Room, #18 Keen Building

[eoas-seminar at lists.fsu.edu]

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&                                                          GFDI COLLOQUIUM                                                                                            &

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Title


“Discovery mathematical models from experimental data"


Speaker


Dr. Alessandro Alla

Department of Mathematics

PUC-Rio, Brazil

Time and Place

11:00AM, Monday, April 22, 2019
Melvin Stern Seminar/Reading Room
18 Keen Building
Refreshments will be served at 10:30AM


ABSTRACT: In this talk, we will present two recent techniques to discover mathematical models from data using machine learning techniques. In the first part of the talk, we advocate the use of Dynamic Mode Decomposition (DMD), an equation-free method, to approximate the data with a linear model. DMD is a spatio-temporal matrix decomposition of a data matrix that correlates spatial features while simultaneously associating the activity with periodic temporal behavior. With this decomposition, one can obtain a reduced dimensional surrogate model and use for future state predictions or extrapolate missing information from the data. In the second part, we address the problem of discovering nonlinear ODEs and PDEs from data. We will show that we can recover the mathematical problem by means of sparse optimization methods such as LASSO and RIDGE regression. Examples and applications of the methods will be showed during the talk.

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