Search Results for author: Yanming Shen

Found 4 papers, 3 papers with code

First Place Solution of KDD Cup 2021 & OGB Large-Scale Challenge Graph Prediction Track

3 code implementations15 Jun 2021 Chengxuan Ying, Mingqi Yang, Shuxin Zheng, Guolin Ke, Shengjie Luo, Tianle Cai, Chenglin Wu, Yuxin Wang, Yanming Shen, Di He

In this technical report, we present our solution of KDD Cup 2021 OGB Large-Scale Challenge - PCQM4M-LSC Track.

Do Transformers Really Perform Bad for Graph Representation?

3 code implementations9 Jun 2021 Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu

Our key insight to utilizing Transformer in the graph is the necessity of effectively encoding the structural information of a graph into the model.

Graph Classification Graph Regression +1

Breaking the Expressive Bottlenecks of Graph Neural Networks

1 code implementation14 Dec 2020 Mingqi Yang, Yanming Shen, Heng Qi, BaoCai Yin

Recently, the Weisfeiler-Lehman (WL) graph isomorphism test was used to measure the expressiveness of graph neural networks (GNNs), showing that the neighborhood aggregation GNNs were at most as powerful as 1-WL test in distinguishing graph structures.

Graph Property Prediction

Deep Learning on Traffic Prediction: Methods, Analysis and Future Directions

no code implementations18 Apr 2020 Xueyan Yin, Genze Wu, Jinze Wei, Yanming Shen, Heng Qi, Bao-Cai Yin

The purpose of this paper is to provide a comprehensive survey on deep learning-based approaches in traffic prediction from multiple perspectives.

Traffic Prediction

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