Reviews: Full-Gradient Representation for Neural Network Visualization

Updates based on author feedback: Given that the authors added the digit flipping experiments and obtained good results (albeit with different choices of post-processing) I am increasing my score to a 7. However, ***the increased score is based on good faith that the authors will add the following to their paper***: (1) I think it would be extremely helpful to practitioners if the authors exposed how different choices of post-processing affected the results. What happens to the digit flipping experiments when sign information is discarded? What happens to Remove & Retrain when sign information is retained? Please be as up front as possible about the caveats; practitioners should be made aware that the choice of post-processing is something they need to pay close attention to, or the method may be used in a way that gives misleading results (as mentioned, we have seen this happen before with Guided Backprop).