Clean-state prediction in diffusion models for turbulent spatiotemporal systems improves rollout stability and reduces long-horizon error compared to velocity- and noise-based objectives.
Benchmarking autoregressive conditional diffusion models for turbulent flow simulation,
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Target Parameterization in Diffusion Models for Nonlinear Spatiotemporal System Identification
Clean-state prediction in diffusion models for turbulent spatiotemporal systems improves rollout stability and reduces long-horizon error compared to velocity- and noise-based objectives.