Home Join AIG News Competitions JSM 2020 [JSM 2021]
Aug 7-12, 2021
Astrostatistics sessions at JSM
INDEX | AIG meeting | Student Paper Award | Statistical Challenges in Cosmology | Other sessions
We will use an Astrostatistics Interest Group Slack channel to ease communication between the audience and the speakers at the various sessions. In order to be added to this channel, please contact one of the office bearers or write to aigamstat @ gmail.
AIG Annual Meeting
Date TBD
The business meeting of the AIG is to be held on TBD
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Session 220444
Date TBD
Astrostatistics Interest Group: Student Paper Award – Topic Contributed Papers
Information about Student Paper competition
Astrostatistics Special Interest Group
Organizer(s): Sara Algeri, University of Minnesota
Chair(s): Vinay Kashyap, Center for Astrophysics | Harvard & Smithsonian
- GHOST: Using Only Host Galaxy Information to Accurately Associate and Distinguish Supernovae
Alex Gagliano, University of Illinois Urbana-Champaign - X-Ray-to-Radio Offset Inference from Low-Count X-Ray Jets
Karthik Reddy, UMaryland - Modeling unresolved binaries of open clusters in the color-magnitude diagram
Lu Li, Shanghai Astronomical Observatory - Assessment of Supervised Machine Learning for Atmospheric Retrieval of Exoplanets
Matt Nixon, University of Cambridge Clare College - Reducing ground-based astrometric errors with Gaia and Gaussian processes
Willow Fox-Fortino, University of Pennsylvania
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Session 220603
Date TBD
Statistical Challenges in Cosmology – Topic Contributed Papers
The era of precision cosmology has brought many statistical challenges to the fore of the field. In this session a mixed group of astronomer/statistician speakers will discuss a variety of modern “cosmostatistical” problems.
Sponsored by the Section on Non-parametric Statistics
Organizer(s): Collin Politsch (CMU)
Chair(s): Jessi Cisewski-Kehe (Madison)
- Learning to predict structure formation in the Universe
Yin Li (Flatiron Institute CCA) - Three-dimensional cosmography of the high-redshift Universe using intergalactic absorption
Collin Politsch (CMU) - Stratified Learning: A general-purpose method for supervised learning under covariate shift with applications to observational cosmology
Maximilian Autenrieth (Imperial College) - Cosmological Parameter Inference in Photometric Surveys: An Inverse Problem
Markus Rau (CMU) - Discussant
Chad Schafer (CMU)
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Other Sessions
TBC
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Other events of interest
TBD