Sequential Design Based on Mutual Information for Computer Experiments - Joakim Beck, KAUST

Sequential Design Based on Mutual Information for Computer Experiments - Joakim Beck, KAUST

Alan Turing Institute via YouTube Direct link

A practical issue with the MI algorithm

10 of 19

10 of 19

A practical issue with the MI algorithm

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Sequential Design Based on Mutual Information for Computer Experiments - Joakim Beck, KAUST

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  1. 1 Intro
  2. 2 Outline
  3. 3 Problem setting
  4. 4 GP emulation
  5. 5 Sequential adaptive designs
  6. 6 ALM and ALC
  7. 7 Greedy mutual information criterion
  8. 8 MI sequential design algorithm
  9. 9 Designing sensor placements (Krause et al., 2008)
  10. 10 A practical issue with the MI algorithm
  11. 11 Mutual Information for Computer Experiments (MICE)
  12. 12 A nugget parameter for smoothing
  13. 13 The improvement in terms of robustness
  14. 14 A visualisation of the design selection
  15. 15 A comparison of the computational cost
  16. 16 Numerical results: 4-D Oscillatory Function
  17. 17 Numerical results: 7-D Piston Simulation
  18. 18 Case study tsunami modelling
  19. 19 An extension: MICE in GP optimisation (optim-MICE)

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