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Tutorial 3: Linear dynamical systems and the Kalman Filter

This tutorial covers how to infer a latent model when our states are continuous. Particular attention is paid to the Kalman filter and it's mathematical foundation.


Overview of this tutorial:

  • Review linear dynamical systems
  • Learn about and implement the Kalman filter
  • Explore how the Kalman filter can be used to smooth data from an eye-tracking experiment
Topics covered in this lesson
  • Linear dynamical systems
  • Kalman Filtering
  • Fitting eye gaze data
  • Review on Gaussian joint, marginal, and conditional distributions
  • Kalman smoothing
  • The Expectation-Maximization (EM) Algorithm

Experience with Python Programming Language.

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