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Abstract: When deploying a machine learning model to a new environment, we often encounter the distribution shift problem - meaning the target data distribution is different from the model's training ...

Abstract: Test-time augmentation—the aggregation of predictions across transformed versions of a test input—is a common practice in image classification. Traditionally, predictions are combined using ...

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