Heterogeneous temporal graph neural network

Y Fan, M Ju, C Zhang, Y Ye - Proceedings of the 2022 SIAM international …, 2022‏ - SIAM
Graph neural networks (GNNs) have been broadly studied on dynamic graphs for their
representation learning, majority of which focus on graphs with homogeneous structures in …

Hypergraph contrastive learning for drug trafficking community detection

T Ma, Y Qian, C Zhang, Y Ye - 2023 IEEE International …, 2023‏ - ieeexplore.ieee.org
In recent decades, due to the lucrative profits, the crime of drug trafficking has evolved with
modern technologies. Social media, as one of the popular online platforms, have become …

Malicious repositories detection with adversarial heterogeneous graph contrastive learning

Y Qian, Y Zhang, N Chawla, Y Ye… - Proceedings of the 31st …, 2022‏ - dl.acm.org
GitHub, as the largest social coding platform, has attracted an increasing number of
cybercriminals to disseminate malware by posting malicious code repositories. To address …

Dual-level Hypergraph Contrastive Learning with Adaptive Temperature Enhancement

Y Qian, T Ma, C Zhang, Y Ye - Companion Proceedings of the ACM Web …, 2024‏ - dl.acm.org
Inspired by the success of graph contrastive learning, researchers have begun exploring the
benefits of contrastive learning over hypergraphs. However, these works have the following …

MSGNN: Multi-scale Spatio-temporal Graph Neural Network for epidemic forecasting

M Qiu, Z Tan, BK Bao - Data Mining and Knowledge Discovery, 2024‏ - Springer
Infectious disease forecasting has been a key focus and proved to be crucial in controlling
epidemic. A recent trend is to develop forecasting models based on graph neural networks …

[PDF][PDF] Adapting meta knowledge with heterogeneous information network for covid-19 themed malicious repository detection

Y Qian, Y Zhang, Y Ye, C Zhang - International Joint Conference on …, 2021‏ - par.nsf.gov
As cyberattacks caused by malware have proliferated during the pandemic, building an
automatic system to detect COVID-19 themed malware in social coding platforms is in urgent …

PANDORA: deep graph learning based COVID-19 infection risk level forecasting

S Yu, F **a, Y Wang, S Li… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
Coronavirus disease 2019 (COVID-19) as a global pandemic causes a massive disruption
to social stability that threatens human life and the economy. An effective forecasting system …

Dr. emotion: Disentangled representation learning for emotion analysis on social media to improve community resilience in the COVID-19 era and beyond

M Ju, W Song, S Sun, Y Ye, Y Fan, S Hou… - Proceedings of the Web …, 2021‏ - dl.acm.org
During the pandemic caused by coronavirus disease (COVID-19), social media has played
an important role by enabling people to discuss their experiences and feelings of this global …

[HTML][HTML] Methods for Infectious Disease Risk Assessments in Megacities Using the Urban Resilience Theory

H Wang, C Cao, X Ma, Y Ma - Sustainability, 2023‏ - mdpi.com
Since the 20th century began, the world has witnessed the emergence of contagious
diseases such as Severe Acute Respiratory Syndrome (SARS), H1N1 influenza, and the …

[ספר][B] Graph Representation Learning Techniques for the Combat Against Online Abusive Activity

Y Qian - 2024‏ - search.proquest.com
With the growing prevalence of the Internet, abusive behaviors on online platforms have
surged in recent decades. These online abusers take advantage of the popularity and …