The paper “Identification of an influence network using ensemble-based filtering
for Hawkes processes driven by count data“, co-authored by Naratip Santitissadeekorn, Sylvain Delahaies, and Dave Lloyd, has been accepted for publication in Physica D. In the paper, they model event-driven dynamics on a network by a multidimensional Hawkes process. They then develop a novel ensemble-based filtering approach for a time-series of count data (i.e., data that provides the number of events per unit time for each node in the network) that not only tracks the influence network structure over time but also approximates the uncertainty via ensemble spread. Their method is demonstrated for large networks using both synthetic and real-world email communication data. Pre-publication version available (link here). The screenshot below shows Figure 11 from their paper.