649 citations · 1.7k across the 57 of their papers we have counts for
10 papers · 1 filter
Deep Multimodal Fusion by Channel Exchanging
Yikai Wang, Wenbing Huang, Fuchun Sun +3
Deep multimodal fusion by using multiple sources of data for classification or regression has exhibited a clear advantage over the unimodal counterpart on various applications. Yet…
On Self-Distilling Graph Neural Network
Yuzhao Chen, Yatao Bian, Xi Xiao +3
Recently, the teacher-student knowledge distillation framework has demonstrated its potential in training Graph Neural Networks (GNNs). However, due to the difficulty of training o…
Graph Information Bottleneck for Subgraph Recognition
Junchi Yu, Tingyang Xu, Yu Rong +3
Given the input graph and its label/property, several key problems of graph learning, such as finding interpretable subgraphs, graph denoising and graph compression, can be attribu…
Tackling Over-Smoothing for General Graph Convolutional Networks
Wenbing Huang, Yu Rong, Tingyang Xu +2
Increasing the depth of GCN, which is expected to permit more expressivity, is shown to incur performance detriment especially on node classification. The main cause of this lies i…
Inverse Graph Identification: Can We Identify Node Labels Given Graph Labels?
Tian Bian, Xi Xiao, Tingyang Xu +4
Graph Identification (GI) has long been researched in graph learning and is essential in certain applications (e.g. social community detection). Specifically, GI requires to predic…
Self-Supervised Graph Transformer on Large-Scale Molecular Data
Yu Rong, Yatao Bian, Tingyang Xu +4
How to obtain informative representations of molecules is a crucial prerequisite in AI-driven drug design and discovery. Recent researches abstract molecules as graphs and employ G…
Multi-View Graph Neural Networks for Molecular Property Prediction
Hehuan Ma, Yatao Bian, Yu Rong +5
The crux of molecular property prediction is to generate meaningful representations of the molecules. One promising route is to exploit the molecular graph structure through Graph…
Spectral Graph Attention Network with Fast Eigen-approximation
Heng Chang, Yu Rong, Tingyang Xu +4
Variants of Graph Neural Networks (GNNs) for representation learning have been proposed recently and achieved fruitful results in various fields. Among them, Graph Attention Networ…
Graph Representation Learning via Graphical Mutual Information Maximization
Zhen Peng, Wenbing Huang, Minnan Luo +4
The richness in the content of various information networks such as social networks and communication networks provides the unprecedented potential for learning high-quality expres…
Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks
Tian Bian, Xi Xiao, Tingyang Xu +4
Social media has been developing rapidly in public due to its nature of spreading new information, which leads to rumors being circulated. Meanwhile, detecting rumors from such mas…