Learning Representations of Galaxies from Simulations and Observations - Suchetha Cooray

Explore the application of machine learning and data science techniques to galaxy formation and evolution in this 28-minute conference talk by Suchetha Cooray from Nagoya University. Discover how astrostatistics and advanced data analysis tools are revolutionizing our understanding of galaxies through large-scale surveys, integral field unit spectroscopy, and multi-wavelength imaging. Learn about the potential of outlier detection algorithms in identifying anomalous galaxies and the importance of linking observational data with theoretical models, including cosmological simulations. Gain insights into the broader context of the "Galaxy Evolution in the Age of Machine Learning" conference, which aims to translate data-driven results into physical understanding and advance the field of galaxy formation physics.

Learning representations of galaxies from simulations & observations ▸ Suchetha Cooray (Nagoya U)