A General Framework for Uncertainty Estimation in Deep Learning

16 Jul 2019Antonio LoquercioMattia SegùDavide Scaramuzza

Neural networks predictions are unreliable when the input sample is out of the training distribution or corrupted by noise. Being able to detect such failures automatically is fundamental to integrate deep learning algorithms into robotics... (read more)

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