Online Graph Learning from Time-Varying Structural Equation Models

Topology identification is an important problem across many disciplines, since it reveals pairwise interactions among entities and can be used to interpret graph data. In many scenarios, however, this (unknown) topology is time-varying, rendering the problem even harder. In this paper, we focus on a time-varying version of the structural...

Real-time travel time prediction framework for departure time and route advice

Heavily used urban networks remain a challenge for travel time prediction because traffic flow is rarely homogeneous and is also subject to a wide variety of disturbances. Various models, some of which use traffic flow theory and some of which are data driven, have been developed to predict traffic flow and travel times. Many of these perform...