Scattering networks on the sphere for scalable and rotationally equivariant spherical CNNs
Convolutional neural networks (CNNs) constructed natively on the sphere have been
developed recently and shown to be highly effective for the analysis of spherical data. While …
developed recently and shown to be highly effective for the analysis of spherical data. While …
Constrained inference through posterior projections
Bayesian approaches are appealing for constrained inference problems by allowing a
probabilistic characterization of uncertainty, while providing a computational machinery for …
probabilistic characterization of uncertainty, while providing a computational machinery for …