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Los Alamos National Laboratory
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Jointly training on simulation and experimental data unlocks balanced prediction in physical systems, outperforming sequential transfer and preserving crucial simulation-only knowledge.
Round-trip consistency allows generative models to self-assess their rollout errors, achieving remarkable accuracy without the need for ensembles or ground truth data.
