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    title = "Training physics-based machine-learning parameterizations with gradient-free ensemble Kalman methods",
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    id = "record",
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    title = {An efficient Bayesian approach to learning droplet collision kernels: Proof of concept using "Cloudy", a new n-moment bulk microphysics scheme},
    year = "2022",
    url = "https://resolver.caltech.edu/CaltechAUTHORS:20220207-89642000",
    id = "record",
    doi = "10.1002/essoar.10510248.1"
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    title = "Ensemble-Based Experimental Design for Targeted High-Resolution Simulations to Inform Climate Models",
    year = "2022",
    url = "https://resolver.caltech.edu/CaltechAUTHORS:20220119-572479000",
    id = "record",
    doi = "10.1002/essoar.10510142.1"
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