In temporal (or event-based) networks, time is a continuous axis, with real-valued time
coordinates for each node and edge. Computing a layout for such graphs means …

Hybrid graph representations combine two or more network visualization techniques in a
unique drawing, simultaneously leveraging their strong traits. Since their introduction in the …

In temporal (event-based) networks, time is a continuous axis, with real-valued time
coordinates for each node and edge. Computing a layout for such graphs means …

Querying time series based on their relations is a crucial part of multiple time series analysis.
By retrieving and understanding time series relations, analysts can easily detect anomalies …

We present HoloGraphs, a novel approach for physically representing, explaining,
exploring, and interacting with dynamic networks. HoloGraphs addresses the challenges of …

Conventional dynamic networks represent network changes via a discrete sequence of
timeslices, which usually entails loss of information on fine-grained dynamics. Recently …

In temporal (or event-based) networks, time is a continuous axis, with real-valued time
coordinates for each node and edge. Computing a layout for such graphs means …