48 citations · 55 across the 6 of their papers we have counts for
6 papers
Spectral Heterogeneous Graph Convolutions via Positive Noncommutative Polynomials
Mingguo He, Zhewei Wei, Shikun Feng +4
Heterogeneous Graph Neural Networks (HGNNs) have gained significant popularity in various heterogeneous graph learning tasks. However, most existing HGNNs rely on spatial domain-ba…
Label Information Enhanced Fraud Detection against Low Homophily in Graphs
Yuchen Wang, Jinghui Zhang, Zhengjie Huang +9
Node classification is a substantial problem in graph-based fraud detection. Many existing works adopt Graph Neural Networks (GNNs) to enhance fraud detectors. While promising, cur…
Layout-aware Webpage Quality Assessment
Anfeng Cheng, Yiding Liu, Weibin Li +6
Identifying high-quality webpages is fundamental for real-world search engines, which can fulfil users' information need with the less cognitive burden. Early studies of \emph{webp…
Graph4Rec: A Universal Toolkit with Graph Neural Networks for Recommender Systems
Weibin Li, Mingkai He, Zhengjie Huang +4
In recent years, owing to the outstanding performance in graph representation learning, graph neural network (GNN) techniques have gained considerable interests in many real-world…
LiteGEM: Lite Geometry Enhanced Molecular Representation Learning for Quantum Property Prediction
Shanzhuo Zhang, Lihang Liu, Sheng Gao +6
In this report, we (SuperHelix team) present our solution to KDD Cup 2021-PCQM4M-LSC, a large-scale quantum chemistry dataset on predicting HOMO-LUMO gap of molecules. Our solution…
Multimodal and Contrastive Learning for Click Fraud Detection
Weibin Li, Qiwei Zhong, Qingyang Zhao +2
Advertising click fraud detection plays one of the vital roles in current E-commerce websites as advertising is an essential component of its business model. It aims at, given a se…