All Outputs (2)

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.

Shape tracing: An extension of sphere tracing for 3D non-convex collision in protein docking (2020)
Presentation / Conference Contribution
Leach, A., Rudden, L. S., Bond-Taylor, S., Brigham, J. C., Degiacomi, M. T., & Willcocks, C. G. (2020, December). Shape tracing: An extension of sphere tracing for 3D non-convex collision in protein docking. Presented at 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE)

This paper presents an algorithm, similar to implicit sphere tracing, that ray marches 3D non-convex shapes for efficient collision detection. Instead of finding points on the surface where individual rays strike, an entire shape is marched in unison... Read More about Shape tracing: An extension of sphere tracing for 3D non-convex collision in protein docking.