At the collision of coarse graining and sampling theory, we have multi-fidelity modeling, which is an attempt to do tries to harness the efficiency of lower-precision and higher-precision models together adaptively in some sense. 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.
Multi fidelity models
Data-driven coarse graining. Also multi-scale models.
2020-08-24 – 2022-01-20
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