Classifier-free guidance trades off sample quality and diversity in conditional diffusion models by combining scores from jointly trained conditional and unconditional models.
Deep unsupervised learning using nonequilibrium thermodynamics
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Introduces an SDE-based framework for score-based generative modeling that unifies prior methods, enables predictor-corrector sampling and neural ODE likelihoods, and achieves SOTA unconditional image generation on CIFAR-10.
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Classifier-Free Diffusion Guidance
Classifier-free guidance trades off sample quality and diversity in conditional diffusion models by combining scores from jointly trained conditional and unconditional models.
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Score-Based Generative Modeling through Stochastic Differential Equations
Introduces an SDE-based framework for score-based generative modeling that unifies prior methods, enables predictor-corrector sampling and neural ODE likelihoods, and achieves SOTA unconditional image generation on CIFAR-10.