7 citations · 7 across the 7 of their papers we have counts for
5 papers · 1 filter
A Compact, Coherent Representation of Stellar Surface Variation in the Spectral Domain
Lily L. Zhao, Megan E. Bedell, David W. Hogg +1
Time-varying inhomogeneities on stellar surfaces constitute one of the largest sources of radial velocity (RV) error for planet detection and characterization. We show that stellar…
Improving Radial Velocities by Marginalizing over Stars and Sky: Achieving 30 m/s RV Precision for APOGEE in the Plate Era
Andrew K. Saydjari, Douglas P. Finkbeiner, Adam J. Wheeler +7
The radial velocity catalog from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) is unique in its simultaneously large volume and high precision as a result of…
Is machine learning good or bad for the natural sciences?
David W. Hogg, Soledad Villar
Machine learning (ML) methods are having a huge impact across all of the sciences. However, ML has a strong ontology - in which only the data exist - and a strong epistemology - in…
NotPlaNET: Removing False Positives from Planet Hunters TESS with Machine Learning
Valentina Tardugno Poleo, Nora Eisner, David W. Hogg
Differentiating between real transit events and false positive signals in photometric time series data is a bottleneck in the identification of transiting exoplanets, particularly…
Frizzle: Combining spectra or images by forward modeling
David W. Hogg, Andrew R. Casey
When there are many observations of an astronomical source - many images with different dithers, or many spectra taken at different barycentric velocities - it is standard practice…