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Latent Variable Energy Based Models

Alfredo Canziani via YouTube

Overview

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This course examines latent variable energy-based models, focusing on free-energy formulations, temperature-dependent training, loss functionals, conditional models, learned manifolds, and decoder design. It also uses PyTorch notation and discusses selecting the latent size.

Syllabus

– Welcome to class
– Zero Temperature Limit ZTL free energy recap
– warmer Free energy
– Infinite Temperature Limit
– Free energy, example y = Y[23]
– Free energy, example y = Y[10]
– Free energy, example y = 0, 0
– Nomenclature and PyTorch
– Training!
– Loss functionals
– ZTL vs. varmer temperature training
– Conditional case
– Untrained model manifold
– Energy function Ex, y, z
– Trained model manifold
– Learning the Decoder
– Choosing the latent size
– And that was it

Taught by

Alfredo Canziani

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