4 papers
Connecting Jensen-Shannon and Kullback-Leibler Divergences: A New Bound for Representation Learning
Reuben Dorent, Polina Golland, William Wells
Mutual Information (MI) is a fundamental measure of statistical dependence widely used in representation learning. While direct optimization of MI via its definition as a Kullback-…
A Unified Deep Learning Framework for Motion Correction in Medical Imaging
Jian Wang, Razieh Faghihpirayesh, Danny Joca +2
Deep learning has shown significant value in medical image registration for motion correction, however, current techniques are either limited by the type and range of motion they c…
SpaER: Learning Spatio-temporal Equivariant Representations for Fetal Brain Motion Tracking
Jian Wang, Razieh Faghihpirayesh, Polina Golland +1
In this paper, we introduce SpaER, a pioneering method for fetal motion tracking that leverages equivariant filters and self-attention mechanisms to effectively learn spatio-tempor…
InterNeRF: Scaling Radiance Fields via Parameter Interpolation
Clinton Wang, Peter Hedman, Polina Golland +2
Neural Radiance Fields (NeRFs) have unmatched fidelity on large, real-world scenes. A common approach for scaling NeRFs is to partition the scene into regions, each of which is ass…