Dynamical Survival Analysis with Controlled Latent States. (arXiv:2401.17077v1 [stat.ML])

We consider the task of learning individual-specific intensities of counting
processes from a set of static variables and irregularly sampled time series.
We introduce a novel modelization approach in which the intensity is the
solution to a controlled differential equation. We first design a neural
estimator by building on neural controlled differential equations. In a second
time, we show that our model can be linearized in the signature space under
sufficient regularity conditions, yielding a signature-based estimator which we
call …

analysis arxiv building design differential differential equation equation intensity novel processes series set solution stat.ml survival time series variables