Reactive graphs enable efficient MCMC inference in probabilistic programming languages by automatically tracking and selectively recomputing data dependencies during sampling.
A Probabilistic Epidemiological Model for Infectious Diseases: The Case of COVID-19 at Global-Level
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Reactive Graphs for Efficient Markov Chain Monte Carlo Inference in Probabilistic Programming Languages
Reactive graphs enable efficient MCMC inference in probabilistic programming languages by automatically tracking and selectively recomputing data dependencies during sampling.