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MNIST using carlini code from git

• Accuracy without dropout = 99.15%
• Accuracy with dropout = 97.59%
• Absolute mean uncertainty on test data = 0.021
• Absolute mean uncertainty on adversarial = 0.224
• Accuracy of dropout on whitebox attack = 0.08
• Accuracy of dropout on graybox attack =

CIFAR-10 using carlini code from git

• Accuracy without dropout = 86.94%
• Accuracy with dropout = 86.54%
• Absolute mean uncertainty on test data = 0.003
• Absolute mean uncertainty on adversarial = 0.005
• Accuracy of dropout on whitebox attack = 0.08
• Accuracy of dropout on graybox attack =