Explanatory Masks for Neural Network Interpretability. (arXiv:1911.06876v1 [cs.LG])
Neural network interpretability is a vital component for applications across a wide variety of domains. In such cases it is often useful to analyze a network which has already been trained for its specific purpose. In this work, we develop a method to produce explanation masks for pre-trained networks. The mask localizes the most important…