CMU Advanced NLP 2022 - Latent Variable Models

CMU Advanced NLP 2022 - Latent Variable Models

Graham Neubig via YouTube Direct link

Introduction

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1 of 20

Introduction

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CMU Advanced NLP 2022 - Latent Variable Models

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  1. 1 Introduction
  2. 2 Types of Variables
  3. 3 Latent Variable Models
  4. 4 Loss Function
  5. 5 Variational inference
  6. 6 Regularized Autoencoder
  7. 7 Sampling
  8. 8 ancestral sampling
  9. 9 conditioned language models
  10. 10 Motivation for latent variables
  11. 11 Training VAEs
  12. 12 Aggressive inference network learning
  13. 13 Latent variables
  14. 14 Discrete latent variables
  15. 15 Reparameterization
  16. 16 Random Sampling
  17. 17 Reparameterization Trick
  18. 18 Gumball Softmax
  19. 19 Gumball Function
  20. 20 Application Examples

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