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5 Semi-Supervised Learning BVM Tutorial: Advanced Deep Learning Methods David Zimmerer, Division of Medical Image Computing Author Division Semi-Supervised Learning 02.11.16 | Page2 2 | David Zimmerer, Division of Medical Image Computing

  1. 5 Semi-Supervised Learning BVM Tutorial: Advanced Deep Learning Methods David Zimmerer, Division of Medical Image Computing

  2. Author Division Semi-Supervised Learning 02.11.16 | Page2 2 | David Zimmerer, Division of Medical Image Computing

  3. Author Division Semi-Supervised Learning 02.11.16 | Page3 3 | David Zimmerer, Division of Medical Image Computing

  4. Author Division Semi-Supervised Learning 02.11.16 | Page4 4 | David Zimmerer, Division of Medical Image Computing

  5. Author Division Semi-Supervised Learning 02.11.16 | Page5 5 | David Zimmerer, Division of Medical Image Computing

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  8. Author Division Semi-Supervised Learning 02.11.16 | Page8 8 | David Zimmerer, Division of Medical Image Computing

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  14. Author Division Semi-Supervised Learning 02.11.16 | Page14 14 | David Zimmerer, Division of Medical Image Computing

  15. Author Division Semi-Supervised Learning 02.11.16 | Page15 15 | David Zimmerer, Division of Medical Image Computing

  16. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page16 16 | David Zimmerer, Division of Medical Image Computing

  17. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page17 z x Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 17 | David Zimmerer, Division of Medical Image Computing

  18. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page18 z x Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 18 | David Zimmerer, Division of Medical Image Computing

  19. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page19 z x Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 19 | David Zimmerer, Division of Medical Image Computing

  20. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page20 μ z σ x x Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 20 | David Zimmerer, Division of Medical Image Computing

  21. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page21 μ z z σ x x Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 21 | David Zimmerer, Division of Medical Image Computing

  22. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page22 μ z z σ x x x’ Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 22 | David Zimmerer, Division of Medical Image Computing

  23. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page23 μ z z σ x x x’ MSE Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 23 | David Zimmerer, Division of Medical Image Computing

  24. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page24 z x Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 24 | David Zimmerer, Division of Medical Image Computing

  25. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page25 z x Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 25 | David Zimmerer, Division of Medical Image Computing

  26. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page26 National Park y z x Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 26 | David Zimmerer, Division of Medical Image Computing

  27. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page27 y z x Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 27 | David Zimmerer, Division of Medical Image Computing

  28. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page28 y z x Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 28 | David Zimmerer, Division of Medical Image Computing

  29. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page29 → Unlabeled Data y z x Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 29 | David Zimmerer, Division of Medical Image Computing

  30. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page30 → Unlabeled Data y z y’ x x Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 30 | David Zimmerer, Division of Medical Image Computing

  31. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page31 → Unlabeled Data μ σ y z y’ x x Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 31 | David Zimmerer, Division of Medical Image Computing

  32. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page32 → Unlabeled Data μ z σ y z y’ x x Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 32 | David Zimmerer, Division of Medical Image Computing

  33. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page33 → Unlabeled Data μ z σ y z y’ x x x’ Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 33 | David Zimmerer, Division of Medical Image Computing

  34. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page34 → Unlabeled Data μ z σ y z y’ x x x’ MSE Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 34 | David Zimmerer, Division of Medical Image Computing

  35. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page35 → Labeled Data y z x Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 35 | David Zimmerer, Division of Medical Image Computing

  36. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page36 → Labeled Data y z y x x Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 36 | David Zimmerer, Division of Medical Image Computing

  37. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page37 → Labeled Data y z y’ y x x Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 37 | David Zimmerer, Division of Medical Image Computing

  38. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page38 → Labeled Data μ σ y z y’ y x x Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 38 | David Zimmerer, Division of Medical Image Computing

  39. Author Division Semi-Supervised Variational Autoencoder 02.11.16 | Page39 → Labeled Data μ z σ y z y’ y x x Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014. 39 | David Zimmerer, Division of Medical Image Computing

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