10.1k citations · 17.4k across the 69 of their papers we have counts for
10 papers · 1 filter
Cyclic Label Propagation for Graph Semi-supervised Learning
Zhao Li, Yixin Liu, Zhen Zhang +3
Graph neural networks (GNNs) have emerged as effective approaches for graph analysis, especially in the scenario of semi-supervised learning. Despite its success, GNN often suffers…
Graph Geometry Interaction Learning
Shichao Zhu, Shirui Pan, Chuan Zhou +3
While numerous approaches have been developed to embed graphs into either Euclidean or hyperbolic spaces, they do not fully utilize the information available in graphs, or lack the…
SciSummPip: An Unsupervised Scientific Paper Summarization Pipeline
Jiaxin Ju, Ming Liu, Longxiang Gao +1
The Scholarly Document Processing (SDP) workshop is to encourage more efforts on natural language understanding of scientific task. It contains three shared tasks and we participat…
Model Extraction Attacks on Graph Neural Networks: Taxonomy and Realization
Bang Wu, Xiangwen Yang, Shirui Pan +1
Machine learning models are shown to face a severe threat from Model Extraction Attacks, where a well-trained private model owned by a service provider can be stolen by an attacker…
Medical Code Assignment with Gated Convolution and Note-Code Interaction
Shaoxiong Ji, Shirui Pan, Pekka Marttinen
Medical code assignment from clinical text is a fundamental task in clinical information system management. As medical notes are typically lengthy and the medical coding system's c…
Multi-Level Graph Convolutional Network with Automatic Graph Learning for Hyperspectral Image Classification
Sheng Wan, Chen Gong, Shirui Pan +2
Nowadays, deep learning methods, especially the Graph Convolutional Network (GCN), have shown impressive performance in hyperspectral image (HSI) classification. However, the curre…
Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning
Sheng Wan, Shirui Pan, Jian Yang +1
Graph-based Semi-Supervised Learning (SSL) aims to transfer the labels of a handful of labeled data to the remaining massive unlabeled data via a graph. As one of the most popular…
Multivariate Relations Aggregation Learning in Social Networks
Jin Xu, Shuo Yu, Ke Sun +4
Multivariate relations are general in various types of networks, such as biological networks, social networks, transportation networks, and academic networks. Due to the principle…
Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks
Zonghan Wu, Shirui Pan, Guodong Long +3
Modeling multivariate time series has long been a subject that has attracted researchers from a diverse range of fields including economics, finance, and traffic. A basic assumptio…
A Survey on Knowledge Graphs: Representation, Acquisition and Applications
Shaoxiong Ji, Shirui Pan, Erik Cambria +2
Human knowledge provides a formal understanding of the world. Knowledge graphs that represent structural relations between entities have become an increasingly popular research dir…