Temporal Network Prediction and Interpretation

Temporal networks refer to networks like physical contact networks whose topology changes over time. Predicting future temporal network is crucial e.g., to forecast the epidemics. Existing prediction methods are either relatively accurate but black-box, or white-box but less accurate. The lack of interpretable and accurate prediction methods...

Online Edge Flow Imputation on Networks

An online algorithm for missing data imputation for networks with signals defined on the edges is presented. Leveraging the prior knowledge intrinsic to real-world networks, we propose a bi-level optimization scheme that exploits the causal dependencies and the flow conservation, respectively via <italic>(i)</italic> a sparse line...

An Automated Detection Framework for Multiple Highway Bottleneck Activations

Highway bottlenecks are responsible for the majority of traffic congestion. Although the problem of bottleneck detection is not new, contemporary methods have not solved the problem thoroughly with regards to bottleneck locations, activation time, and related congestion tracking. These elements are essential for identifying and characterizing a...