Use-cases for inverted PCA

A lot of people know of PCA for it's ability to reduce the dimensionality of a dataset. It can turn a wide dataset into a thin one, while hopefully only a limited amount of information. But what about doing it the other way around as well? Can you turn the thin representation into a wide one again? And if so, what might be a use-case for that?

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