38 citations · 64 across the 7 of their papers we have counts for
8 papers
Graph Neural Networks for Low-Energy Event Classification & Reconstruction in IceCube
R. Abbasi, M. Ackermann, J. Adams +380
IceCube, a cubic-kilometer array of optical sensors built to detect atmospheric and astrophysical neutrinos between 1 GeV and 1 PeV, is deployed 1.45 km to 2.45 km below the surfac…
An update on the development of ASPIRED
Marco C Lam, Robert J Smith, Josh Veitch-Michaelis +2
We are reporting the updates in version 0.2.0 of the Automated SpectroPhotometric REDuction (ASPIRED) pipeline, designed for common use on different instruments. The default settin…
Learnings from Frontier Development Lab and SpaceML -- AI Accelerators for NASA and ESA
Siddha Ganju, Anirudh Koul, Alexander Lavin +3
Research with AI and ML technologies lives in a variety of settings with often asynchronous goals and timelines: academic labs and government organizations pursue open-ended resear…
The WAGGS project -- III. Discrepant mass-to-light ratios of Galactic globular clusters at high metallicity
H. Dalgleish, S. Kamann, C. Usher +10
Observed mass-to-light ratios (M/L) of metal-rich globular clusters (GCs) disagree with theoretical predictions. This discrepancy is of fundamental importance since stellar populat…
Assessing the influence of one astronomy camp over 50 years
Hannah Dalgleish, Josh Veitch-Michaelis
The International Astronomical Youth Camp has benefited thousands of lives during its 50-year history. We explore the pedagogy behind this success, review a survey taken by more th…
RASCAL: Towards automated spectral wavelength calibration
Josh Veitch-Michaelis, Marco C Lam
Wavelength calibration is a routine and critical part of any spectral work-flow, but many astronomers still resort to matching detected peaks and emission lines by hand. We present…