At the collision of coarse graining and sampling theory and variational inference, we have multi-fidelity modeling, which is an attempts to harness the efficiency of lower-precision and higher-precision models together. This name is a Machine Learning name; I presume that this concept has been invented many times under other names, which I will add when I learn them. Possibly one of those names is learnable coarse graining
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