1 citations · 1 across the 3 of their papers we have counts for
3 papers
Unmixing Noise from Hawkes Process to Model Learned Physiological Events
Guillaume Staerman, Virginie Loison, Thomas Moreau
Physiological signal analysis often involves identifying events crucial to understanding biological dynamics. Traditional methods rely on handcrafted procedures or supervised learn…
Flexible Parametric Inference for Space-Time Hawkes Processes
Emilia Siviero, Guillaume Staerman, Stephan Clémençon +1
Many modern spatio-temporal data sets, in sociology, epidemiology or seismology, for example, exhibit self-exciting characteristics, triggering and clustering behaviors both at the…
FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels
Guillaume Staerman, Cédric Allain, Alexandre Gramfort +1
Temporal point processes (TPP) are a natural tool for modeling event-based data. Among all TPP models, Hawkes processes have proven to be the most widely used, mainly due to their…