16 citations · 24 across the 3 of their papers we have counts for
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cs.LG2022★ 16 cited
Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs
Chenxiao Yang, Qitian Wu, Jiahua Wang +1
Graph neural networks (GNNs), as the de-facto model class for representation learning on graphs, are built upon the multi-layer perceptrons (MLP) architecture with additional messa…
cs.LG2022★ 5 cited
Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks
Chenxiao Yang, Qitian Wu, Junchi Yan
We study a new paradigm of knowledge transfer that aims at encoding graph topological information into graph neural networks (GNNs) by distilling knowledge from a teacher GNN model…
cs.LG2022★ 3 cited
Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment
Chenxiao Yang, Qitian Wu, Qingsong Wen +3
The goal of sequential event prediction is to estimate the next event based on a sequence of historical events, with applications to sequential recommendation, user behavior analys…