In-Distribution Interpretability for Challenging Modalities

1 Jul 2020Cosmas HeißRon LevieCinjon ResnickGitta KutyniokJoan Bruna

It is widely recognized that the predictions of deep neural networks are difficult to parse relative to simpler approaches. However, the development of methods to investigate the mode of operation of such models has advanced rapidly in the past few years... (read more)

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