839 citations · 1.4k across the 11 of their papers we have counts for
11 papers
Learning To Sample the Meta-Paths for Social Event Detection
Congbo Ma, Hu Wang, Zitai Qiu +5
Social media data is inherently rich, as it includes not only text content, but also users, geolocation, entities, temporal information, and their relationships. This data richness…
Graph Neural Networks for Brain Graph Learning: A Survey
Xuexiong Luo, Jia Wu, Jian Yang +7
Exploring the complex structure of the human brain is crucial for understanding its functionality and diagnosing brain disorders. Thanks to advancements in neuroimaging technology,…
Discriminative Graph-level Anomaly Detection via Dual-students-teacher Model
Fu Lin, Xuexiong Luo, Jia Wu +4
Different from the current node-level anomaly detection task, the goal of graph-level anomaly detection is to find abnormal graphs that significantly differ from others in a graph…
ProcessGPT: Transforming Business Process Management with Generative Artificial Intelligence
Amin Beheshti, Jian Yang, Quan Z. Sheng +6
Generative Pre-trained Transformer (GPT) is a state-of-the-art machine learning model capable of generating human-like text through natural language processing (NLP). GPT is traine…
State of the Art and Potentialities of Graph-level Learning
Zhenyu Yang, Ge Zhang, Jia Wu +9
Graphs have a superior ability to represent relational data, like chemical compounds, proteins, and social networks. Hence, graph-level learning, which takes a set of graphs as inp…
DAGAD: Data Augmentation for Graph Anomaly Detection
Fanzhen Liu, Xiaoxiao Ma, Jia Wu +7
Graph anomaly detection in this paper aims to distinguish abnormal nodes that behave differently from the benign ones accounting for the majority of graph-structured instances. Rec…
Graph-level Neural Networks: Current Progress and Future Directions
Ge Zhang, Jia Wu, Jian Yang +6
Graph-structured data consisting of objects (i.e., nodes) and relationships among objects (i.e., edges) are ubiquitous. Graph-level learning is a matter of studying a collection of…
Single-stage Rotate Object Detector via Two Points with Solar Corona Heatmap
Beihang Song, Jing Li, Shan Xue +4
Oriented object detection is a crucial task in computer vision. Current top-down oriented detection methods usually directly detect entire objects, and not only neglecting the auth…
A Comprehensive Survey on Graph Anomaly Detection with Deep Learning
Xiaoxiao Ma, Jia Wu, Shan Xue +5
Anomalies represent rare observations (e.g., data records or events) that deviate significantly from others. Over several decades, research on anomaly mining has received increasin…
A Comprehensive Survey on Community Detection with Deep Learning
Xing Su, Shan Xue, Fanzhen Liu +9
A community reveals the features and connections of its members that are different from those in other communities in a network. Detecting communities is of great significance in n…
Deep Learning for Community Detection: Progress, Challenges and Opportunities
Fanzhen Liu, Shan Xue, Jia Wu +6
As communities represent similar opinions, similar functions, similar purposes, etc., community detection is an important and extremely useful tool in both scientific inquiry and d…