793 citations · 3.2k across the 19 of their papers we have counts for
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cs.LG2018★ 374 cited
How Powerful are Graph Neural Networks?
Keyulu Xu, Weihua Hu, Jure Leskovec +1
Graph Neural Networks (GNNs) are an effective framework for representation learning of graphs. GNNs follow a neighborhood aggregation scheme, where the representation vector of a n…
cs.LG2018★ 454 cited
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels
Bo Han, Quanming Yao, Xingrui Yu +5
Deep learning with noisy labels is practically challenging, as the capacity of deep models is so high that they can totally memorize these noisy labels sooner or later during train…