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Ensemble methods combine the predictions of multiple models to improve performance, but they require significantly higher computation costs at inference time.
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Fine-tuning can distort pretrained features and underperform out-of-distribution
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Diverse weight averaging for out-of-distribution generalization
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The impact of averaging logits over probabilities on ensembles of neural networks
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