Skip to content. | Skip to navigation

Personal tools


You are here: Home / Meetings / All Meetings / "Applied Statistical Methods in Astronomy: Gaussian Processes and Machine Learning"

"Applied Statistical Methods in Astronomy: Gaussian Processes and Machine Learning"

This is a Special Session within the 231th meeting of the American Astronomical Society and is sponsored by the AAS Working Group on Astroinformatics and Astrostatistics and the CHASC International Center for Astrostatistics. The goal of this special session is to review advances in the newly popular methods of gaussian processes and machine learning, to present applications to data, and to discuss current issues and future perspectives. These methods have applications across the entire spectrum of astronomical research and are being rapidly developed. The invited talks include discussion of application of gaussian processes to time-series spectra in exoplanet research, machine learning techniques to quantify variability states of a micro-quasar, machine learning application in cosmology, and handling multi-catalogs source detection. We also intend to have an associated poster session allowing contributions from the entire community. The session schedule will allow for a discussion, questions and input from the audience.
When 10 January 2018
from 12:30 PM to 12:30 PM
Where National Harbor MD USA
Add event to calendar vCal


Confirmed Speakers:
Dan Foreman-Mackey (University of Washington)
Daniela Huppenkothen (NYU)
Ian Czekala (Stanford)
Michelle (Hicks) Ntampaka (CMU)
Tamas Budavari (JHU)

More information about this event…