Bayesian Neural Hawkes Process for Event Uncertainty Prediction. (arXiv:2112.14474v2 [cs.LG] UPDATED)

Event data consisting of time of occurrence of the events arises in several
real-world applications. Recent works have introduced neural network based
point processes for modeling event-times, and were shown to provide
state-of-the-art performance in predicting event-times. However, neural point
process models lack a good uncertainty quantification capability on
predictions. A proper uncertainty quantification over event modeling will help
in better decision making for many practical applications. Therefore, we
propose a novel point process model, Bayesian Neural Hawkes process (BNHP) …

arxiv bayesian event prediction process uncertainty