Machine Learning at the Flatiron Institute Seminar: Jean Ponce

Title: Physical models and machine learning for Photography and Astronomy

Abstract: We live in an era of data-driven approaches to image analysis, where modeling is sometimes considered obsolete. I will propose in this talk giving back to accurate physical models of image formation their rightful place next to machine learning in the overall processing and interpretation pipeline, and discuss two applications: super-resolution and high-dynamic range imaging from raw photographic bursts, and exoplanet detection and characterization in direct imaging at high contrast. This is joint work with Theo Bodrito, Yann Dubois de Mont-Marin, Thomas Eboli, Olivier Flasseur, Anne-Marie Lagrange, Maud Langlois, Bruno Lecouat, and Julien Mairal.