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Gas-Theft Suspect Detection among Boiler Room Users: A Data-Driven Approach

IEEE TKDE

Federated Digital Gateway: Methodologies, Tools and Applications

IEEE Intelligent Systems

Predicting Citywide Crowd Flows in Irregular Regions Using Multi-View Graph Convolutional Networks

IEEE TKDE, 2020

Spatio-Temporal Meta Learning for Urban Traffic Prediction

IEEE TKDE

Federated Forest

IEEE TBD

Predicting and ranking box office revenue of movies based on big data

Information Fusion

Urban flow prediction from spatiotemporal data using machine learning: A survey

Information Fusion

Flow Prediction in Spatio-Temporal Networks Based on Multitask Deep Learning

Predicting flows (e.g. the traffic of vehicles, crowds and bikes), consisting of the in-out traffic at a node and transitions between different nodes, in a spatio-temporal network plays an important role in transportation systems. However, this is a …

Predicting Citywide Crowd Flows Using Deep Spatio-Temporal Residual Networks

AI 2018

Predicting citywide crowd flows using deep spatio-temporal residual networks

Forecasting the flow of crowds is of great importance to traffic management and public safety, and very challenging as it is affected by many complex factors, including spatial dependencies (nearby and distant), temporal dependencies (closeness, …