3.2k citations · 9.8k across the 51 of their papers we have counts for
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A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
Dan Hendrycks, Kevin Gimpel
We consider the two related problems of detecting if an example is misclassified or out-of-distribution. We present a simple baseline that utilizes probabilities from softmax distr…
Early Methods for Detecting Adversarial Images
Dan Hendrycks, Kevin Gimpel
Many machine learning classifiers are vulnerable to adversarial perturbations. An adversarial perturbation modifies an input to change a classifier's prediction without causing the…
Adjusting for Dropout Variance in Batch Normalization and Weight Initialization
Dan Hendrycks, Kevin Gimpel
We show how to adjust for the variance introduced by dropout with corrections to weight initialization and Batch Normalization, yielding higher accuracy. Though dropout can preserv…
Gaussian Error Linear Units (GELUs)
Dan Hendrycks, Kevin Gimpel
We propose the Gaussian Error Linear Unit (GELU), a high-performing neural network activation function. The GELU activation function is , where the standard Gaussian…