Last Updated: 20191228

[AAS 235] Ask-A-Statistician Table

Sunday-Wednesday, January 5-8, 2020

Afternoon
#CSC, Chandra Booth, CfA Street, Exhibit Hall
Convention Center, Honolulu HI

hea-www.harvard.edu/AstroStat/aas235/AaS.html
| Description | Schedule | Sign-up | Other events of interest | Contacts | changelog |

Description

We are organizing a rolling Ask-A-Statistician discussion table during the winter meeting of the American Astronomical Society at Honolulu, HI (Jan 4-8 2020). We will have several statisticians and astrostatisticians present at designated times to discuss several topics with interested astronomers, ranging from the mathematical foundations of Bayesian analysis to Machine Learning.

Schedule
Day/Time Topics People
Sun Jan 5
1:30-3pm
Statistical inference, Approximate Bayesian Computation, Deep Learning, Machine Learning, non-parametrics, Bayesian parametrics, calibration and systematics Chad Schafer (Statistics, CMU)
Herman Marshall (CXC/MIT)
Mon Jan 6
1:30-3pm
Bayesian analysis, Bayesian inference, exoplanet detectability, high-dimensional and non-parametric methods Bo Ning (Statistics, Yale)
Gwen Eadie (Astro & Statistics, UToronto)
Tue Jan 7
3:30-5:30pm
Outlier detection, supervised classification (neural nets, random forests), hierarchical Bayes, Gaussian Linear Models, deconvolution, Ising models Rafael Martinez-Galarce (CXC/CfA)
Katy McKeough (Statistics, Harvard)
Wed Jan 8
1:30-3:30pm
MCMC, source detection, Type I & II errors, upper limits, Bayesian analysis, calibration and systematics, classification, outliers Herman Marshall (CXC/MIT)
Rafael Martinez-Galarce (CXC/CfA)

Astronomers attending AAS 235 are welcome to drop in at the Chandra Booth to discuss topics of interest with the statisticians and astrostatisticians present during these times. In order that we may plan for the sessions better, please fill out this google docs sign-up sheet. We ask that you let us know when you plan to stop by the Table, and a brief description of the data analysis issue you want to discuss. We have found through several trials that it often takes multiple iterations before a question can be properly understood and a useful answer formulated.

Other Events of interest at AAS 235

There are several sessions and talks during AAS 235 that are of interest to astrostatistics and astroinformatics. Here we list those we are aware of. If there is something we have missed, please let us know.

Sessions
Working Group on Astrostatistics and Astroinformatics Splinter Session into the 2020s, Sun Jan 5 9:30am-11:30am
 
Workshops
The 2nd AAS Chandra/CIAO Workshop (Day 1 of 2), Fri Jan 3 9:00am-5:00pm
The 2nd AAS Chandra/CIAO Workshop (Day 2 of 2), Sat Jan 4 9:00am-5:00pm
Using Python and Astropy for Astronomical Data Analysis, Sat Jan 4 9:00am-5:30pm
Hands-on Machine Learning for Astronomers: Artificial Intelligence for Big-Data Astronomy, Tue Jan 7 1:00pm-5:00pm
 
Talks
#136 on Computation, Data Handling, and Image Analysis, Sun Jan 5 10:00am-11:30am
#154 on Surveys and Large Programs I, Sun Jan 5, 2:00pm-3:30pm
#232 on Surveys and Large Programs II, Mon Jan 6, 10:00am-11:30am
#329 on The Solar System: Surveys, Instrumentation, Computation, Data Handling, Tue Jan 7 10:00am-11:30am
#357 on Machine Learning and Data Visualization Frontiers for Astronomy, Tue Jan 7 2:00pm-3:30pm
 
#136.02 Defining regions that contain complex astronomical structures McKeough, Meng, Kashyap, Siemiginowska, van Dyk, Yang, & Zezas Sun Jan 5 10:10am-10:30am
#136.04 A New Method for Point Source Function Reconstruction in Undersampled Images with Noise Mitigation Symons, Zemcov, Crill, Cheng, & Venuto Sun Jan 5 10:40am-10:50am
#154.02 Strong X-ray Flaring Objects Observed with Chandra Irwin & Lin Sun Jan 5 2:10pm-2:20pm
#225.03 Identifying Activity-sensitive Spectral Lines: A Bayesian Variable Selection Approach, Ning Mon Jan 6, 10:30am-10:40am
#232.02 Systematic Serendipity: Automated Anomaly Detection and Prioritization for Large Datasets, Giles & Walkowicz Mon Jan 6 10:10am-10:30am
#266.05 Two-point statistics without bins: A continuous-function generalization of the correlation function estimator for large-scale structure, Storey-Fisher & Hogg Mon Jan 6, 3:00pm-3:10pm
#357.02 Science with Large Survey Datasets: Opportunities and Challenges, Belim Tue Jan 7 2:20pm-2:40pm
#357.03 Mining TESS Data for Anomalous Light Curves, Martinez-Galarza & Crake Tue Jan 7 2:40pm-2:50pm
#357.04 Disks-Hosting Members of Columba-Carina Found Using Disk Detective and Virtual Reality Tue Jan 7 2:50pm-3:00pm
 
iPosters-Plus
#287 on Computation, Data Handling, Image Analysis & Catalogs, Mon Jan 6, 5:30pm-6:30pm
 
#220.01 Impulsive energy deposition into coronae through self-organized criticality, Kashyap, Kim, Heseltine, et al., Mon Jan 6 9:00am-9:10am
#287.03 Detrending light curves using strictly periodic variable stars, Prsa & Horvat Mon Jan 6 5:50pm-6:00pm
 
iPosters
#313 on Computation, Data Handling, Image Analysis/Surveys and Large Programs & Catalogs, Tue Jan 7 9:00am-10:00am
 
#313.02 Advances in Image Fidelity: Radio Interferometer and Single-Dish Data Combination Plunkett Tue Jan 7 9:00am-10:00am
#313.03 PhoSim: A Tool to Simulate Astronomical Images One Photon at a Time, Peterson, Dutta, Jernigan, Remocaldo, & Sembroski Tue Jan 7 9:00am-10:00am
#313.08 A Random Forest Approach to Identifying Young Stellar Object Candidates in the Lupus Star-Forming Region Melton Tue Jan 7 9:00am-10:00am
 
Posters
#109 on Computation, Data Handling, and Image Analysis, Sun Jan 5 9:00am-10:00am
#386 on Machine Learning and Data Visualization Frontiers for Astronomy, Tue Jan 7 5:30pm-6:30pm
 
#109.04 Enabling Fast Bayesian Exoplanet Atmospheric Retrievals using AWS Bourque, Stevenson, & Filippazzo Sun Jan 5 9:00am-10:00am
#109.05 Deep Learning for 21cm Tomography Makinen, Lancaster, Ho, & Melchior Sun Jan 5 9:00am-10:00am
#109.11 Applying Machine Learning to VLITE Radio Transient Searches, Van Der Horst, Polisensky, Peters, Clarke, & Kassim Sun Jan 5 9:00am-10:00am
#109.15 astroML: a Python package for Machine Learning for Astronomy and its wider ecosystem Sipocz, Connolly, Ivezic, Vander Plas, & Gray Sun Jan 5 9:00am-10:00am
#109.16 The Weirdest Objects in the X-ray Universe: A Machine Learning Approach Freeman & Martinez-Galarza Sun Jan 5 9:00am-10:00am
#109.17 Using TESS Data to Detect Astrophysical Transients, Jayaraman, Fausnaugh, Villasenor, & Ricker Sun Jan 5 9:00am-10:00am
#109.22 Techniques for Reducing Catastrophic Outlier Redshift Estimates in Large-Scale Surveys, Wyatt & Singal Sun Jan 5 9:00am-10:00am
#109.23 Implementation of Semi-Supervised Learning with Siamese Networks for Object Detection, Roussi & Nord Sun Jan 5 9:00am-10:00am
#109.24 Identifying and Repairing Catastrophic Errors in Galaxy Properties Using Dimensionality Reduction, Hovis-Afflerbach, Steinhardt, Brammer, & Capak Sun Jan 5 9:00am-10:00am
#109.25 Diffusion Entropy as a tool for time-intermittent events: complexity in flares, bursts, and jets, Pease Sun Jan 5 9:00am-10:00am
#109.26 Engineering a Web-Based Interface to Predict the Unknown Physical Characteristics of Main-Sequence Stars, Perea Rojas & Bellinger Sun Jan 5 9:00am-10:00am
#109.28 An Update on Cross-matching CSC 2.0 with Other Major Catalogs by CXC, Rots et al. Sun Jan 5 9:00am-10:00am
#170.17 Simulating the Recovery Rate of Eclipsing Binaries in Star Clusters with LSST, Bowen & Geller Sun Jan 5 5:30pm-6:30pm
#170.20 Systematic Discovery and Classification of TESS Eclipsing Binaries, Birky, Davenport, & Brandt Sun Jan 5 5:30pm-6:30pm
#102.22 Accuracy of Student-led Analysis of Pulsar Search Data, Priddy, Dew, Burke, & Dempsey Sun Jan 5, 9:00am-10:00am
#273.05 Bayesian Cross Matching of High Proper Motion Stars in Gaia DR2 and Other Sources, Medan & Lepine Mon Jan 6 5:30pm-6:30pm
#275.05 The effect of measurement errors on estimating power law distribution parameters and implications for measuring the IMF, Christian & Ginsburg, Mon Jan 6 5:30pm-6:30pm
#386.01 Predicting planets from orbital perturbations using a Bayesian N-body retrieval and machine learning, Pearson Tue Jan 7 5:30pm-6:30pm
#386.02 A Recommendation Algorithm to Predict Giant Exoplanet Host Stars Using Stellar Elemental Abundances, Hinkel, Unterborn, Kane, & Somers Tue Jan 7 5:30pm-6:30pm
#386.05 Galaxy Cluster Membership with Machine Learning, Narayanan & Ntampaka Tue Jan 7 5:30pm-6:30pm
#386.06 Cosmological constraints with deep learning from KiDS-450 weak lensing maps, Fluri et al. Tue Jan 7 5:30pm-6:30pm
#386.07 deepCR: Cosmic Ray Rejection with Deep Learning, Zhang & Bloorm Tue Jan 7 5:30pm-6:30pm
#386.08 Deep learning for the Zwicky Transient Facility: real/bogus classification and identification of fast-moving objects, Duev Tue Jan 7 5:30pm-6:30pm
#386.09 Modeling Color-Magnitude Diagrams with Bayesian Neural Flows, Cranmer, Galvez, Anderson, Spergel, & Ho Tue Jan 7 5:30pm-6:30pm
#386.10 Spectral Cleaning: Artifact Detection and Repair in Spectral Data, Finkbeiner Tue Jan 7 5:30pm-6:30pm
 
Hyperwall Talks
A Sharper Grasp of X-Ray Images by Vinay Kashyap & Katy McKeough, Wed Jan 8 12:15pm

Contacts

Organizers
Vinay Kashyap (v k a s h y a p at c f a . h a r v a r d .edu)
Aneta Siemiginowska (a s i e m i g i n o w s k a at c f a . h a r v a r d .edu)
Statisticians
Bo Ning (b o . n i n g at y a l e . edu)
Chad Schafer (c s c h f e r at c m u . edu)
Katy McKeough (k a t y . m c k e o u g h at g m a i l .com)
Astrostatisticians
Gwen Eadie (g w e n . e a d i e at u t o r o n t o .ca)
Herman Marshall (h e r m a n m at s p a c e . m i t .edu)
Rafael Martinez-Galarce (j m a r t i n e at c f a . h a r v a r d .edu)

changelog

2019-dec-20: started page
2019-dec-21: public
2019-dec-23: added more related talks and posters of interest
2019-dec-24: more talks and posters, added sign-up link to menu
2019-dec-27: added link to AAS events listing: https://aas.org/events/2019-12/ask-statistician-discussion-table-aas-235
2019-dec-28: typo fixes


| AAS235 | CfA | CHASC | AIG | WGAA |
Ask-a-Statistician
Jan 5-8 2020
Afternoon HST
#CSC, Chandra Booth,
CfA St., Exhibit Hall

Description

Sign-up

Schedule
Sun Jan 5
Mon Jan 6
Tue Jan 7
Wed Jan 8

Other Events

Contacts
changelog





CfA / CHASC / AIG / WGAA