Lecture 28 - Variational Inference#

Objectives#

  • Explain the Kullback-Leibler divergence and its properties.

  • Explain the mean-field posterior approximation.

  • Explain the low-rank covariance approximation.

  • Pose mathematically the variational inference problem in a convenient form.

  • Solve the variational inference problem using stochastic gradient descent.