Overview
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Explore the fundamentals of normalizing flows in this comprehensive lecture on density estimation and machine learning techniques. Delve into key concepts including the change of variables formula, increasing triangular maps, and autoregressive models. Learn about neural autoregressive flows and the Glow architecture. Discover how to apply these methods for interpolation tasks, with a focus on linear interpolation. Gain valuable insights into advanced machine learning algorithms and their applications in density estimation and generative modeling.
Syllabus
Introduction
Density estimation
Normalizing flows
Agenda
Change of variables formula
Increasing triangular maps
Normalising flows
Autoregressive models
Neural autoregressive flows
Glow
Interpolation
Linear interpolation
Taught by
Pascal Poupart