Using Uncertainty to Interpret your Model
Published in
7 min readJul 30, 2018
As deep neural networks (DNN) become more powerful, their complexity increases. This complexity introduces new challenges, including model interpretability.
Interpretability is crucial in order to build models that are more robust and resistant to adversarial attacks. Moreover, designing a model for a new, not well researched domain is challenging and being able to interpret what the model…
