
Jointly Attacking Graph Neural Network and its Explanations
Graph Neural Networks (GNNs) have boosted the performance for many graph...
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SemiSupervised GraphtoGraph Translation
Graph translation is very promising research direction and has a wide ra...
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Graph Convolutional Networks against DegreeRelated Biases
In recent years, Graph Convolutional Networks (GCNs) show competitive pe...
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Knowing your FATE: Friendship, Action and Temporal Explanations for User Engagement Prediction on Social Apps
With the rapid growth and prevalence of social network applications (App...
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Graph Structure Learning for Robust Graph Neural Networks
Graph Neural Networks (GNNs) are powerful tools in representation learni...
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Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values
Multivariate time series (MTS) forecasting is widely used in various dom...
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Node Injection Attacks on Graphs via Reinforcement Learning
Realworld graph applications, such as advertisements and product recomm...
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Robust Graph Neural Network Against Poisoning Attacks via Transfer Learning
Graph neural networks (GNNs) are widely used in many applications. Howev...
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Joint Modeling of Dense and Incomplete Trajectories for Citywide Traffic Volume Inference
Realtime traffic volume inference is key to an intelligent city. It is ...
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Learning from Multiple Cities: A MetaLearning Approach for SpatialTemporal Prediction
Spatialtemporal prediction is a fundamental problem for constructing sm...
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Modeling SpatialTemporal Dynamics for Traffic Prediction
Spatialtemporal prediction has many applications such as climate foreca...
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Deep MultiView SpatialTemporal Network for Taxi Demand Prediction
Taxi demand prediction is an important building block to enabling intell...
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Xianfeng Tang
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