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Introduction to Gaussian Processes Neil D. Lawrence GPMC 6th - PowerPoint PPT Presentation

Apr 19, 2023 •125 likes •1.95k views

Introduction to Gaussian Processes Neil D. Lawrence GPMC 6th February 2017 Book Rasmussen and Williams (2006) Outline The Gaussian Density Covariance from Basis Functions Outline The Gaussian Density Covariance from Basis Functions The

  1. Stages to Derivation of the Posterior ◮ Multiply likelihood by prior ◮ they are “exponentiated quadratics”, the answer is always also an exponentiated quadratic because exp( a 2 ) exp( b 2 ) = exp( a 2 + b 2 ). ◮ Complete the square to get the resulting density in the form of a Gaussian. ◮ Recognise the mean and (co)variance of the Gaussian. This is the estimate of the posterior.

  2. Multivariate Regression Likelihood ◮ Noise corrupted data point y i = w ⊤ x i , : + ǫ i

  3. Multivariate Regression Likelihood ◮ Noise corrupted data point y i = w ⊤ x i , : + ǫ i ◮ Multivariate regression likelihood:  n  1  − 1 � 2 �  �  y i − w ⊤ x i , : p ( y | X , w ) = (2 πσ 2 ) n / 2 exp       2 σ 2    i = 1

  4. Multivariate Regression Likelihood ◮ Noise corrupted data point y i = w ⊤ x i , : + ǫ i ◮ Multivariate regression likelihood:  n  1  − 1 � 2 �  �  y i − w ⊤ x i , : p ( y | X , w ) = (2 πσ 2 ) n / 2 exp       2 σ 2    i = 1 ◮ Now use a multivariate Gaussian prior: 1 − 1 � � 2 α w ⊤ w p ( w ) = exp p (2 πα ) 2

  5. Two Dimensional Gaussian ◮ Consider height, h / m and weight, w / kg . ◮ Could sample height from a distribution: p ( h ) ∼ N (1 . 7 , 0 . 0225) ◮ And similarly weight: p ( w ) ∼ N (75 , 36)

  6. Height and Weight Models p ( w ) p ( h ) h / m w / kg Gaussian distributions for height and weight.

  7. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  8. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  9. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  10. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  11. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  12. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  13. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  14. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  15. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  16. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  17. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  18. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  19. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  20. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  21. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  22. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  23. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  24. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  25. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  26. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  27. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  28. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  29. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m Samples of height and weight

  30. Independence Assumption ◮ This assumes height and weight are independent. p ( h , w ) = p ( h ) p ( w ) ◮ In reality they are dependent (body mass index) = w h 2 .

  31. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m

  32. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m

  33. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m

  34. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m

  35. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m

  36. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m

  37. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m

  38. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m

  39. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m

  40. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m

  41. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m

  42. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m

  43. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m

  44. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m

  45. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m

  46. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m

  47. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m

  48. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m

  49. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m

  50. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m

  51. Sampling Two Dimensional Variables Marginal Distributions Joint Distribution p ( h ) w / kg p ( w ) h / m

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