BayesLDM: A Domain-Specific Language for Probabilistic Modeling of Longitudinal Data. (arXiv:2209.05581v1 [cs.LG])

In this paper we present BayesLDM, a system for Bayesian longitudinal data
modeling consisting of a high-level modeling language with specific features
for modeling complex multivariate time series data coupled with a compiler that
can produce optimized probabilistic program code for performing inference in
the specified model. BayesLDM supports modeling of Bayesian network models with
a specific focus on the efficient, declarative specification of dynamic
Bayesian Networks (DBNs). The BayesLDM compiler combines a model specification
with inspection of available data …

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