4 papers
Is Your Conditional Diffusion Model Actually Denoising?
Daniel Pfrommer, Zehao Dou, Christopher Scarvelis +2
We study the inductive biases of diffusion models with a conditioning-variable, which have seen widespread application as both text-conditioned generative image models and observat…
Sensitivity Analysis for Diffusion Models
Christopher Scarvelis, Justin Solomon
Training a diffusion model approximates a map from a data distribution to the optimal score function for that distribution. Can we differentiate this map? If we could, t…
Closed-Form Diffusion Models
Christopher Scarvelis, Haitz Sáez de Ocáriz Borde, Justin Solomon
Score-based generative models (SGMs) sample from a target distribution by iteratively transforming noise using the score function of the perturbed target. For any finite training s…
Nuclear Norm Regularization for Deep Learning
Christopher Scarvelis, Justin Solomon
Penalizing the nuclear norm of a function's Jacobian encourages it to locally behave like a low-rank linear map. Such functions vary locally along only a handful of directions, mak…