"Additional layers can try to detect out-of-distribution problems during runtime."
Wang, Zhao and Chen developed an OOD detection framework that attaches detectors to intermediate layers of deep neural networks and uses early stopping during inference. Their research directly supports the sidenote about layering additional detectors around running models to identify unexpected inputs before completing the full computation.
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