AT ask Descriptions and Training Settings

We provide a detailed description of all tasks and some additional details on the training of MDEQ. The entire dataset is divided into training (50K images) and testing (10K) sets. We use two different training settings for evaluating the MDEQ model on CIFAR-10. In the second setting, we apply data augmentation to the input images (i.e., The dataset we use contains 1.2 million labeled training images from ImageNet [ Each pixel is classified in a 19-way fashion for evaluation. CIFAR-10 classification models were trained on 1 GPU (including the baselines).