Unsupervised Learning - Autoencoding the Targets

Unsupervised Learning - Autoencoding the Targets

Alfredo Canziani via YouTube Direct link

– Reconstruction energies

14 of 20

14 of 20

– Reconstruction energies

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Unsupervised Learning - Autoencoding the Targets

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  1. 1 – 2021 edition disclaimer
  2. 2 – Unsupervised learning and generative models
  3. 3 – Input space interpolation
  4. 4 – Latent space interpolation
  5. 5 – Conditional generative networks
  6. 6 – Style transfer
  7. 7 – Super resolution
  8. 8 – Inpainting
  9. 9 – Caption to image Dall-e
  10. 10 – Definitions: x, y, z
  11. 11 – Recap: conditional latent variable EBM
  12. 12 – Recap: energy function
  13. 13 – Softmin training recap → autoencoder via amortised inference
  14. 14 – Reconstruction energies
  15. 15 – Loss functional
  16. 16 – Under and over complete hidden layer
  17. 17 – Denoising autoencoder
  18. 18 – Nearest neighbourhood denoising autoencoder
  19. 19 – Sparse autoencoder
  20. 20 – Final remarks

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