272 citations · 279 across the 2 of their papers we have counts for
2 papers
cs.LG2020★ 272 cited
XGNN: Towards Model-Level Explanations of Graph Neural Networks
Hao Yuan, Jiliang Tang, Xia Hu +1
Graphs neural networks (GNNs) learn node features by aggregating and combining neighbor information, which have achieved promising performance on many graph tasks. However, GNNs ar…
cs.CL2020★ 7 cited
iCapsNets: Towards Interpretable Capsule Networks for Text Classification
Zhengyang Wang, Xia Hu, Shuiwang Ji
Many text classification applications require models with satisfying performance as well as good interpretability. Traditional machine learning methods are easy to interpret but ha…