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Suppose that model A gets samples from a joint distribution across horizon (trajectories), and model B gets samples from a joint distribution across both horizon and location. Current ensemble functionality for samples would end up with a mix of samples that handle different types of dependency. It would be good to standardize to the "lowest common denominator" so that all ensemble samples have output_type_id values encoding the same type of dependence structure.
The text was updated successfully, but these errors were encountered:
Suppose that model A gets samples from a joint distribution across horizon (trajectories), and model B gets samples from a joint distribution across both horizon and location. Current ensemble functionality for samples would end up with a mix of samples that handle different types of dependency. It would be good to standardize to the "lowest common denominator" so that all ensemble samples have output_type_id values encoding the same type of dependence structure.
The text was updated successfully, but these errors were encountered: