Learning Collective Variables That Reproduce Transition Rates
This work revisits the framework of quantitative coarse graining and identifies the orthogonality condition from Legoll and Lelievre (2010) as a key criterion for constructing CVs that accurately preserve the statistical properties of the original process and introduces a general numerical method for designing neural n...