37 citations · 137 across the 21 of their papers we have counts for
Showing 2017 · cs.LGShow all
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cs.LG2017★ 1 cited
Semi-Supervised Learning with IPM-based GANs: an Empirical Study
Tom Sercu, Youssef Mroueh
We present an empirical investigation of a recent class of Generative Adversarial Networks (GANs) using Integral Probability Metrics (IPM) and their performance for semi-supervised…
cs.LG2017★ 2 cited
Sobolev GAN
Youssef Mroueh, Chun-Liang Li, Tom Sercu +2
We propose a new Integral Probability Metric (IPM) between distributions: the Sobolev IPM. The Sobolev IPM compares the mean discrepancy of two distributions for functions (critic)…
cs.LG2017
Fisher GAN
Youssef Mroueh, Tom Sercu
Generative Adversarial Networks (GANs) are powerful models for learning complex distributions. Stable training of GANs has been addressed in many recent works which explore differe…