∞-Diff: Infinite Resolution Diffusion with Subsampled Mollified States
(2024)
Presentation / Conference Contribution
Bond-Taylor, S., & Willcocks, C. G. (2024, May). ∞-Diff: Infinite Resolution Diffusion with Subsampled Mollified States. Presented at The International Conference on Learning Representations (ICLR), Vienna Austria
This paper introduces ∞-Diff, a generative diffusion model defined in an infinite-dimensional Hilbert space, which can model infinite resolution data. By training on randomly sampled subsets of coordinates and denoising content only at those location... Read More about ∞-Diff: Infinite Resolution Diffusion with Subsampled Mollified States.