You can; but a standard KDE will necessarily retain all of the data (as centers of Gaussian balls – by data here I mean sampled points from the posterior) and compute the full likelihood of the KDE for sampling, so don’t expect much of a speedup over the full posterior. Typically choices of Q are more concise than KDE for efficiency reasons.
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