Hawkes processes

Tuesday, April 24, 2018 - 10:30am - 11:00am
Yao Xie (Georgia Institute of Technology)
Hawkes processes has been a popular point process model for capturing mutual excitation of discrete events. In the network setting, this can capture the mutual influence between nodes, which has a wide range of applications in neural science, social networks, and crime data analysis. In this talk, I will present a statistical change-point detection framework to detect in real-time, a change in the influence using streaming discrete events.
Wednesday, April 25, 2018 - 3:00pm - 3:30pm
Vincent Rivoirard (Université Paris-Dauphine)
Functional connectivity in neuroscience is considered as one of the main features of the neural code. It is nowadays possible to obtain the spike activities of tens to hundreds of neurons simultaneously and the issue is then to infer the functional connectivity thanks to those complex data. To deal with this problem, we consider estimation of sparse local independence graphs by using models based on multivariate Hawkes processes.
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