Physical machine learning for astrophysics: differentiable spherical harmonics; harmonic Bayesian evidence; spherical scattering networks
Date
Nov 2023
Event
Debating the potential of machine learning in astronomical surveys
Location
Paris
France
Jason McEwen
Professor of Astrostatistics
My research interests encompass a wide range of areas across scientific AI (including physics-enhanced AI, geometric AI, statistical AI, generative AI), astrostatistics, Bayesian inference, harmonic analysis, optimisation, and computational techniques. I focus mostly on scientific problems in astrophysics, primarily cosmology, but am also interested in problems in seismology, climate, medical imaging, and computer vision.