Sufficient conditions for the convergence of the Shannon differential entropy

This work revisits and extends results concerning the convergence of the Shannon differential entropy. Concrete connections with the convergence of probability measures in the sense of total variations and (direct and reverse) information divergence are established. In particular, under uniform bounded conditions on the sequence of probability measures, the results stipulate that the convergence in information divergence is sufficient to guarantee the convergence of the differential entropy functional.