ZOPPA at fixed positive temperature converges under minimal assumptions by acting as an exact proximal point method on a smoothed objective, with explicit connections back to the original function and convergence for its sampled version.
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Coupled initial noises in diffusion models, with designed dependence but unchanged marginal Gaussians, improve generated image diversity on Stable Diffusion variants while preserving quality and alignment.
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Convergence of zeroth-order proximal point algorithms in the high-temperature regime
ZOPPA at fixed positive temperature converges under minimal assumptions by acting as an exact proximal point method on a smoothed objective, with explicit connections back to the original function and convergence for its sampled version.
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Couple to Control: Joint Initial Noise Design in Diffusion Models
Coupled initial noises in diffusion models, with designed dependence but unchanged marginal Gaussians, improve generated image diversity on Stable Diffusion variants while preserving quality and alignment.