SPIEDiff uses conditional diffusion models and epinets to robustly learn thermodynamic structure from short-time particle simulations, with quantified epistemic uncertainty.
Modeling materials: continuum, atomistic and multiscale techniques
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SPIEDiff: robust learning of long-time macroscopic dynamics from short-time particle simulations with quantified epistemic uncertainty
SPIEDiff uses conditional diffusion models and epinets to robustly learn thermodynamic structure from short-time particle simulations, with quantified epistemic uncertainty.