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cs.LG2026
Mixture-of-Gaussians-Guided Schedule Design for Brownian Bridge Diffusion Models
Ron Levi, Michael Elad
Brownian Bridge Diffusion Models (BBDM) offer an appealing framework for image restoration and inverse problems by constructing a stochastic bridge from the clean signal directly t…
cs.LG2026
Analyzing and Guiding Zero-Shot Posterior Sampling in Diffusion Models
Roi Benita, Michael Elad, Joseph Keshet
Recovering a signal from its degraded measurements is a long standing challenge in science and engineering. Recently, zero-shot diffusion based methods have been proposed for such…
cs.LG2025
Spectral Analysis of Diffusion Models with Application to Schedule Design
Roi Benita, Michael Elad, Joseph Keshet
Diffusion models (DMs) have emerged as powerful tools for modeling complex data distributions and generating realistic new samples. Over the years, advanced architectures and sampl…