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# Discussion and questions
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* Q: Why does this approach work so well?
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* Q Stefan Kesselheim (SK): Why does this approach work so well?
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* avoids overfitting by avoiding narrow task
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* choice of data augmentation seems to be key to performance, e.g. example given in Fig 6 about color distribution
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* Stephan Bialonski (SB) interessted in self-supervised learning for time series, here pre-text task is hard to properly define
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