Differentiable and accelerated spherical transforms with JAX

Next-generation radio interferometric imaging.

Sparse OPTimisation using state-of-the-art convex optimisation algorithms.

Slepian Scale-Discretised Wavelets in Python

Machine learning assisted marginal likelihood (Bayesian evidence) estimation for Bayesian model selection

Fast and exact spin spherical harmonic transforms

Differentiable and GPU accelerated scattering covariance statistics on the sphere

PyTorch-based radio-interferometric imaging reconstruction package with scalable Bayesian uncertainty quantification relying on data-driven (learned) priors

Proximal Nested Sampling for high-dimensional Bayesian model selection