10.1k citations · 12.1k across the 55 of their papers we have counts for
8 papers · 1 filter
Learning to Propagate for Graph Meta-Learning
Lu Liu, Tianyi Zhou, Guodong Long +2
Meta-learning extracts common knowledge from learning different tasks and uses it for unseen tasks. It can significantly improve tasks that suffer from insufficient training data,…
Attributed Graph Clustering: A Deep Attentional Embedding Approach
Chun Wang, Shirui Pan, Ruiqi Hu +3
Graph clustering is a fundamental task which discovers communities or groups in networks. Recent studies have mostly focused on developing deep learning approaches to learn a compa…
Prototype Propagation Networks (PPN) for Weakly-supervised Few-shot Learning on Category Graph
Lu Liu, Tianyi Zhou, Guodong Long +3
A variety of machine learning applications expect to achieve rapid learning from a limited number of labeled data. However, the success of most current models is the result of heav…
Graph WaveNet for Deep Spatial-Temporal Graph Modeling
Zonghan Wu, Shirui Pan, Guodong Long +2
Spatial-temporal graph modeling is an important task to analyze the spatial relations and temporal trends of components in a system. Existing approaches mostly capture the spatial…
Search Efficient Binary Network Embedding
Daokun Zhang, Jie Yin, Xingquan Zhu +1
Traditional network embedding primarily focuses on learning a continuous vector representation for each node, preserving network structure and/or node content information, such tha…
Attributed Network Embedding via Subspace Discovery
Daokun Zhang, Jie Yin, Xingquan Zhu +1
Network embedding aims to learn a latent, low-dimensional vector representations of network nodes, effective in supporting various network analytic tasks. While prior arts on netwo…
Learning Graph Embedding with Adversarial Training Methods
Shirui Pan, Ruiqi Hu, Sai-fu Fung +3
Graph embedding aims to transfer a graph into vectors to facilitate subsequent graph analytics tasks like link prediction and graph clustering. Most approaches on graph embedding f…
A Comprehensive Survey on Graph Neural Networks
Zonghan Wu, Shirui Pan, Fengwen Chen +3
Deep learning has revolutionized many machine learning tasks in recent years, ranging from image classification and video processing to speech recognition and natural language unde…