Denoising Diffusion Probabilistic Models on SO(3) for Rotational Alignment
(2022)
Presentation / Conference Contribution
Leach, A., Schmon, S. M., Degiacomi, M. T., & Willcocks, C. G. (2022, April). Denoising Diffusion Probabilistic Models on SO(3) for Rotational Alignment. Presented at ICLR 2022 Workshop on Geometrical and Topological Representation Learning
Probabilistic diffusion models are capable of modeling complex data distributions on high-dimensional Euclidean spaces for a range applications. However, many real world tasks involve more complex structures such as data distributions defined on mani... Read More about Denoising Diffusion Probabilistic Models on SO(3) for Rotational Alignment.