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ICLR 2020: Yann LeCun and Energy-Based Models

Machine Learning Street Talk (MLST)

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Understanding Deterministic Models and Latent Variables in Variational Autoencoders

This chapter explores the design of deterministic models similar to variational autoencoders, highlighting the role of latent variables in capturing data structure. It also introduces the re-parameterization trick to enhance backpropagation through sampling in variational methods.

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