10.1k citations · 17.4k across the 69 of their papers we have counts for
10 papers · 1 filter
Learning Multi-level Weight-centric Features for Few-shot Learning
Mingjiang Liang, Shaoli Huang, Shirui Pan +2
Few-shot learning is currently enjoying a considerable resurgence of interest, aided by the recent advance of deep learning. Contemporary approaches based on weight-generation sche…
Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications
Shaoxiong Ji, Shirui Pan, Xue Li +3
Suicide is a critical issue in modern society. Early detection and prevention of suicide attempts should be addressed to save people's life. Current suicidal ideation detection met…
Hyperspectral Image Classification With Context-Aware Dynamic Graph Convolutional Network
Sheng Wan, Chen Gong, Ping Zhong +3
In hyperspectral image (HSI) classification, spatial context has demonstrated its significance in achieving promising performance. However, conventional spatial context-based metho…
Efficient Novelty-Driven Neural Architecture Search
Miao Zhang, Huiqi Li, Shirui Pan +2
One-Shot Neural architecture search (NAS) attracts broad attention recently due to its capacity to reduce the computational hours through weight sharing. However, extensive experim…
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…
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…
Knowledge Transferring via Model Aggregation for Online Social Care
Shaoxiong Ji, Guodong Long, Shirui Pan +4
The Internet and the Web are being increasingly used in proactive social care to provide people, especially the vulnerable, with a better life and services, and their derived socia…
DAGCN: Dual Attention Graph Convolutional Networks
Fengwen Chen, Shirui Pan, Jing Jiang +2
Graph convolutional networks (GCNs) have recently become one of the most powerful tools for graph analytics tasks in numerous applications, ranging from social networks and natural…
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…