Harmonic Analysis

Scalable and Equivariant Spherical CNNs by Discrete-Continuous (DISCO) Convolutions
No existing spherical convolutional neural network (CNN) framework is both computationally scalable and rotationally equivariant. …
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Mapping dark matter on the celestial sphere with weak gravitational lensing
Convergence maps of the integrated matter distribution are a key science result from weak gravitational lensing surveys. To date, …
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Sparse image reconstruction on the sphere: a general approach with uncertainty quantification
Inverse problems defined naturally on the sphere are becoming increasingly of interest. In this article we provide a general framework …
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Sparse Bayesian mass-mapping with uncertainties: Full sky observations on the celestial sphere
To date weak gravitational lensing surveys have typically been restricted to small fields of view, such that the flat-sky approximation …
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Efficient generalized spherical CNNs
Many problems across computer vision and the natural sciences require the analysis of spherical data, for which representations may be …
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Scale-discretised ridgelet transform on the sphere
We revisit the spherical Radon transform, also called the Funk-Radon transform, viewing it as an axisymmetric convolution on the …
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