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Heterogeneous temporal graph neural network
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 …
representation learning, majority of which focus on graphs with homogeneous structures in …
Hypergraph contrastive learning for drug trafficking community detection
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 …
modern technologies. Social media, as one of the popular online platforms, have become …
Malicious repositories detection with adversarial heterogeneous graph contrastive learning
GitHub, as the largest social coding platform, has attracted an increasing number of
cybercriminals to disseminate malware by posting malicious code repositories. To address …
cybercriminals to disseminate malware by posting malicious code repositories. To address …
Dual-level Hypergraph Contrastive Learning with Adaptive Temperature Enhancement
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 …
benefits of contrastive learning over hypergraphs. However, these works have the following …
MSGNN: Multi-scale Spatio-temporal Graph Neural Network for epidemic forecasting
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 …
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
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 …
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
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 …
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
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 …
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 …
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 …
surged in recent decades. These online abusers take advantage of the popularity and …