A Appendix

Method Y ear Family Train T est V alidation (HP/Model Selection) RandNet [11] 2017 AE ensemble Polluted =Train None, fixed - sensitivity analysis on some HPs RDA [48] 2017 AE Polluted =Train Best on Test, other HPs fixed DAGMM [49] 2018 AE & density Clean & Pol.d Disjoint None, fixed - sensitivity on reg. For MNIST, we choose Digit '4' and '5' For CIFAR10, we choose class'automobile' as the inlier-class. The inliers are labeled 0 and outliers are denoted as label 1. The data split and configuration are the same as described in the authors' provided code. With 4-to-8 different HPs each, the total number of configurations, and i.e. models trained, After the first-layer, the number of channels expand at rate of 2 .