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Training Latent Variable Energy-Based Models (LV-EBMs)

Difficulty level
Intermediate
Duration
1:04:48

This tutorial covers the concept of training latent variable energy based models (LV-EBMs) and is is a part of the Deep Learning Course at NYU's Center for Data Science.

Topics covered in this lesson

Chapters: 

00:00 – Welcome to class
01:11 – Zero Temperature Limit (ZTL) free energy recap
05:29 – (warmer) Free energy
15:42 – Infinite Temperature Limit
20:20 – Free energy, example y = Y[23]
25:22 – Free energy, example y = Y[10]
26:41 – Free energy, example y = (0, 0)
28:30 – Nomenclature and PyTorch
34:13 – Training!
35:44 – Loss functionals
46:09 – ZTL vs. varmer temperature training
49:50 – Conditional case
51:47 – Untrained model manifold
54:11 – Energy function E(x, y, z)
56:48 – Trained model manifold
59:54 – Learning the Decoder
1:01:15 – Choosing the latent size
1:03:02 – And that was it