1.7k citations · 2.2k across the 4 of their papers we have counts for
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cs.LG2018★ 223 cited
An empirical study on evaluation metrics of generative adversarial networks
Qiantong Xu, Gao Huang, Yang Yuan +4
Evaluating generative adversarial networks (GANs) is inherently challenging. In this paper, we revisit several representative sample-based evaluation metrics for GANs, and address…
cs.LG2017★ 1.7k cited
On Calibration of Modern Neural Networks
Chuan Guo, Geoff Pleiss, Yu Sun +1
Confidence calibration -- the problem of predicting probability estimates representative of the true correctness likelihood -- is important for classification models in many applic…
cs.LG2016★ 273 cited
Deep Networks with Stochastic Depth
Gao Huang, Yu Sun, Zhuang Liu +2
Very deep convolutional networks with hundreds of layers have led to significant reductions in error on competitive benchmarks. Although the unmatched expressiveness of the many la…