5 citations · 11 across the 3 of their papers we have counts for
6 papers
deep-REMAP: Parameterization of Stellar Spectra Using Regularized Multi-Task Learning
Sankalp Gilda
Traditional spectral analysis methods are increasingly challenged by the exploding volumes of data produced by contemporary astronomical surveys. In response, we develop deep-Regul…
{\sc mirkwood:} Fast and Accurate SED Modeling Using Machine Learning
Sankalp Gilda, Sidney Lower, Desika Narayanan
Traditional spectral energy distribution (SED) fitting codes used to derive galaxy physical properties are often uncertain at the factor of a few level owing to uncertainties in ga…
Astronomical Image Quality Prediction based on Environmental and Telescope Operating Conditions
Sankalp Gilda, Yuan-Sen Ting, Kanoa Withington +6
Intelligent scheduling of the sequence of scientific exposures taken at ground-based astronomical observatories is massively challenging. Observing time is over-subscribed and atmo…
Gamma-ray Bursts as distance indicators through a machine learning approach
Maria Dainotti, Vahé Petrosian, Malgorzata Bogdan +7
Gamma-ray bursts (GRBs) are spectacularly energetic events, with the potential to inform on the early universe and its evolution, once their redshifts are known. Unfortunately, det…
Automatic Kalman-Filter-based Wavelet Shrinkage Denoising of 1D Stellar Spectra
Sankalp Gilda, Zachary Slepian
We propose a non-parametric method to denoise 1D stellar spectra based on wavelet shrinkage followed by adaptive Kalman thresholding. Wavelet shrinkage denoising involves applying…
The first super-Earth Detection from the High Cadence and High Radial Velocity Precision Dharma Planet Survey
Bo Ma, Jian Ge, Matthew Muterspaugh +23
The Dharma Planet Survey (DPS) aims to monitor about 150 nearby very bright FGKM dwarfs (within 50 pc) during 20162020 for low-mass planet detection and characterization using t…