CMU Advanced NLP 2021 - Latent Variable Models

CMU Advanced NLP 2021 - Latent Variable Models

Graham Neubig via YouTube Direct link

Method 1 Sampling

19 of 21

19 of 21

Method 1 Sampling

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CMU Advanced NLP 2021 - Latent Variable Models

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  1. 1 Introduction
  2. 2 Discriminative vs generative models
  3. 3 Types of variables
  4. 4 Loss function
  5. 5 Two tasks
  6. 6 Bias and variance
  7. 7 Evidence lower bound
  8. 8 Procedural training
  9. 9 Questions
  10. 10 Learning the VAE
  11. 11 Generating Sentences
  12. 12 Problems
  13. 13 kl divergence annealing
  14. 14 Free bits
  15. 15 Weaken the decoder
  16. 16 Aggressive inference network learning
  17. 17 Standard variational autoencoder
  18. 18 What are discrete latent variables
  19. 19 Method 1 Sampling
  20. 20 Method 2 Sampling
  21. 21 Method 2 Reparameterization

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