[disgruntledphd2]

Honestly, I think that we're coming at this from very different perspectives.

Single imputation is garbage for accurate inference, as it reduces variance and thus confidence intervals as P(missing) increases.

MI is a useful method for alleviating this bias (though at the cost of a lot more compute).

That's why it gets used, and it's performed extremely well in real world analyses for basically my entire life (and I'm middle-aged now).

> especially in the unsupervised context.

I wouldn't use MI in an unsupervised context (but maybe some people do).