AstroAI Lunch Talks - September 30, 2024 - Liam Connor
30 Sep 2024 - Joshua Wing
The video can be found here: https://www.youtube.com/watch?v=yUP15RHKN7w
Speaker: Liam Connor (Harvard University)
Title: Ill-posed inverse problems in radio astronomy
Abstract: In the past decade, tremendous progress has been made by the computer vision community with respect to the classical ill-posed inverse problems, largely thanks to efficient neural network architectures for reconstruction. These include deblurring, deconvolution and superresolution, image inpainting, and 3D reconstruction. Radio interferometers have battled sparse image reconstruction for decades, relying mostly on iterative algorithms like CLEAN. In this talk, I will describe our work on learning-based methods for imaging in radio interferometry and 3D reconstruction in the context of cosmology. I will discuss the scientific value of super-resolution imaging on the upcoming DSA-2000 radio camera, for example strong gravitational lensing.
Watch the talk below!