Understanding Deep Neural Networks through Input Uncertainties

31 Oct 2018Jayaraman J. ThiagarajanIrene KimRushil AnirudhPeer-Timo Bremer

Techniques for understanding the functioning of complex machine learning models are becoming increasingly popular, not only to improve the validation process, but also to extract new insights about the data via exploratory analysis. Though a large class of such tools currently exists, most assume that predictions are point estimates and use a sensitivity analysis of these estimates to interpret the model... (read more)

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