Unverified50% confidenceOpinionExact time
Diffusion models and score-based methods are particularly attractive for turbulence because they can represent multimodal distributions.
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50%
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Long-term
Relevance
10/27/2026
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VerifiedThe mathematical essence of diffusion models is based on stochastic differential equations and score matching theory, underpinning image generation systems such as Stable Diffusion and DALL-E.76% similarUnverifiedNormalizing flows are a class of deep generative models that construct complex probability distributions by stacking invertible, differentiable transformations, and express densities using the change-of-variables formula combined with the Jacobian determinant.76% similarUnverifiedThe conjugate moment measure proposes using a single convex potential function W to simultaneously characterize the sampling distribution and the transport map, offering a path for generative modeling that differs from mainstream diffusion models.73% similarUnverifiedBoth DALL·E 2 and Stable Diffusion are based on the principles of diffusion models.73% similarUnverifiedDiffusion models natively support parallel prediction across multiple positions, enabling the probability distributions of all answer slots to be obtained at once.72% similar
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