Research map / Probabilistic and scientific modeling / Uncertainty and Gaussian processes
Automated Model Selection with Bayesian Quadrature
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Select likelihood observations by mutual information with posterior model probabilities rather than by evidence-estimation uncertainty | Bayesian quadrature for model selection · Synthetic GP model selection, d=1–5 | fractional error of z1 estimates | Helped |
| Select likelihood observations by mutual information with posterior model probabilities rather than by evidence-estimation uncertainty | Bayesian quadrature for model selection · Quasar DLA model selection, SDSS-III spectra | absolute error of log odds | Helped |
| Use an acquisition function targeting the indicator [z1 > z2] instead of z1 (ablation) | Bayesian quadrature for model choice · Synthetic GP model choice, d=1–2 | fractional error of z1 estimates | Hurt |
| Use an acquisition function targeting the indicator [z1 > z2] instead of z1 (ablation) | Bayesian quadrature for model choice · Synthetic GP model choice, d=2 | fraction of trials selecting the model with higher ground-truth posterior probab | No clear effect |
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