Reconstructing the Galactic merger history with machine learning
Astronomers use machine learning to reconstruct past mergers that the Milky Way experienced.
UR: Using Machine Learning to Identify Transients in the DESI Survey
Today’s undergraduate post talks about how to use machine learning to find transients in galactic spectra!
Disentangling Milky Way Evolution with Disentangled Representation Learning, a New Tool for Chemical Tagging
Chemical tagging without chemical abundances? Today’s authors devise a neural network that ‘disentangles’ chemical abundances from stellar spectra to avoid the uncertainties that often beset chemical taggers.
Meet the AAS Keynote Speakers: Dr. Brian Nord
Machine learning is a powerful tool… but with great power, comes great responsibility. Learn more about it at Dr. Brian Nord’s talk at #AAS237!
Taking better astronomical images, with machine learning!
Too many cool science projects, not enough telescope time. Can machine learning help solve this problem?
Baryonic Physics with Deep Learning
A new, efficient approach to modelling hydrodynamics in cosmological simulations