The discrete diffusion NELBO equals data entropy plus an exact path KL to the oracle reverse process, and the denoiser, cavity, and score parameterizations are three interconvertible coordinates of the unique optimal reverse jump rate.
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SBTG recovers the Jacobian of the nonlinear transition map between brain states by multiplying cross-block scores from denoising models, enabling inference of lag-specific directed interactions in neural population data such as C. elegans calcium imaging.
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What Does a Discrete Diffusion Model Learn?
The discrete diffusion NELBO equals data entropy plus an exact path KL to the oracle reverse process, and the denoiser, cavity, and score parameterizations are three interconvertible coordinates of the unique optimal reverse jump rate.
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Inferring Active Neural Circuits Using Diffusion Scores
SBTG recovers the Jacobian of the nonlinear transition map between brain states by multiplying cross-block scores from denoising models, enabling inference of lag-specific directed interactions in neural population data such as C. elegans calcium imaging.