Multi fidelity models

Data-driven multi-scale sampling

The pun here is too delicious for me not to use this 1885 cartoon; yes I am aware that marital dynamics are more nuanced amongst adherents of the LDS than the gentleman depicted seems to believe.

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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