9.7k citations · 45.3k across the 61 of their papers we have counts for
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Explaining and Harnessing Adversarial Examples
Ian J. Goodfellow, Jonathon Shlens, Christian Szegedy
Several machine learning models, including neural networks, consistently misclassify adversarial examples---inputs formed by applying small but intentionally worst-case perturbatio…
On distinguishability criteria for estimating generative models
Ian J. Goodfellow
Two recently introduced criteria for estimation of generative models are both based on a reduction to binary classification. Noise-contrastive estimation (NCE) is an estimation pro…
An empirical analysis of dropout in piecewise linear networks
David Warde-Farley, Ian J. Goodfellow, Aaron Courville +1
The recently introduced dropout training criterion for neural networks has been the subject of much attention due to its simplicity and remarkable effectiveness as a regularizer, a…