4 papers
Mechanisms of Projective Composition of Diffusion Models
Arwen Bradley, Preetum Nakkiran, David Berthelot +2
We study the theoretical foundations of composition in diffusion models, with a particular focus on out-of-distribution extrapolation and length-generalization. Prior work has show…
Composition and Control with Distilled Energy Diffusion Models and Sequential Monte Carlo
James Thornton, Louis Bethune, Ruixiang Zhang +3
Diffusion models may be formulated as a time-indexed sequence of energy-based models, where the score corresponds to the negative gradient of an energy function. As opposed to lear…
Classifier-Free Guidance is a Predictor-Corrector
Arwen Bradley, Preetum Nakkiran
We investigate the theoretical foundations of classifier-free guidance (CFG). CFG is the dominant method of conditional sampling for text-to-image diffusion models, yet unlike othe…
Step-by-Step Diffusion: An Elementary Tutorial
Preetum Nakkiran, Arwen Bradley, Hattie Zhou +1
We present an accessible first course on diffusion models and flow matching for machine learning, aimed at a technical audience with no diffusion experience. We try to simplify the…