8.1k citations · 13.6k across the 6 of their papers we have counts for
4 papers · 1 filter
Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
Nicolas Papernot, Martín Abadi, Úlfar Erlingsson +2
Some machine learning applications involve training data that is sensitive, such as the medical histories of patients in a clinical trial. A model may inadvertently and implicitly…
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…
Generative Adversarial Networks
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza +5
We propose a new framework for estimating generative models via an adversarial process, in which we simultaneously train two models: a generative model G that captures the data dis…