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Enhancing Transformation-Based Defenses Against Adversarial Attacks with a Distribution Classifier
Furthermore, on the adversarial counterparts, with the image transformation, the resulting shapes of the distribution of softmax are similar to the distributions from the clean images.
Enhancing Transformation-based Defenses using a Distribution Classifier
Furthermore, on the adversarial counterparts, with the image transformation, the resulting shapes of the distribution of softmax are similar to the distributions from the clean images.
Theoretical and Experimental Analysis on the Generalizability of Distribution Regression Network
However, in Kou et al. (2018) and some other works on distribution regression, there is a lack of comprehensive comparative study on both theoretical basis and generalization abilities of the methods.
A Compact Network Learning Model for Distribution Regression
Despite the superior performance of deep learning in many applications, challenges remain in the area of regression on function spaces.
Distribution Regression Network
We introduce our Distribution Regression Network (DRN) which performs regression from input probability distributions to output probability distributions.
