Advances in Distribution Compression - From Kernel Thinning to Stein Thinning

Advances in Distribution Compression - From Kernel Thinning to Stein Thinning

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Stein Thinning in Action: Correcting for Tempering

13 of 14

13 of 14

Stein Thinning in Action: Correcting for Tempering

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Advances in Distribution Compression - From Kernel Thinning to Stein Thinning

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  1. 1 Intro
  2. 2 Motivation: Computational Cardiology
  3. 3 Distribution Compression
  4. 4 Problem Setup
  5. 5 Maximum Mean Discrepancies
  6. 6 Square-root Kernels
  7. 7 Kernel Thinning vs. i.i.d. Sampling: Higher Dimensions
  8. 8 Kernel Thinning vs. Standard MCMC Thinning Posterior inference for systems of ordinary differential equations (ODES) • P-posterior distribution of coupled ODE model parameters given observed data
  9. 9 Compression with Bias Correction
  10. 10 Measuring Distance to P
  11. 11 Stein Thinning Guarantees
  12. 12 Stein Thinning in Action: Correcting for Burn-in Goodwin model of oscillatory enzymatic control
  13. 13 Stein Thinning in Action: Correcting for Tempering
  14. 14 Conclusions

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