A minimum divergence method for model weighting in prediction averaging shows small-sample advantages over stacking and Akaike-style weighting.
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A Divergence-Based Method for Weighting and Averaging Model Predictions
A minimum divergence method for model weighting in prediction averaging shows small-sample advantages over stacking and Akaike-style weighting.
- Detecting Model Misspecification in Bayesian Inverse Problems via Variational Gradient Descent