196 citations · 696 across the 13 of their papers we have counts for
4 papers · 1 filter
Effectively using unsupervised machine learning in next generation astronomical surveys
Itamar Reis, Michael Rotman, Dovi Poznanski +2
In recent years many works have shown that unsupervised Machine Learning (ML) can help detect unusual objects and uncover trends in large astronomical datasets, but a few challenge…
Probabilistic Random Forest: A machine learning algorithm for noisy datasets
Itamar Reis, Dalya Baron, Sahar Shahaf
Machine learning (ML) algorithms become increasingly important in the analysis of astronomical data. However, since most ML algorithms are not designed to take data uncertainties i…
Redshifted broad absorption line quasars found via machine-learned spectral similarity
Itamar Reis, Dovi Poznanski, Patrick B. Hall
We report the discovery of 31 new redshifted broad absorption line quasars (RSBALs) from the Sloan Digital Sky Survey (SDSS). The number of previously known such objects is 19. The…
Detecting outliers and learning complex structures with large spectroscopic surveys - a case study with APOGEE stars
Itamar Reis, Dovi Poznanski, Dalya Baron +2
In this work we apply and expand on a recently introduced outlier detection algorithm that is based on an unsupervised random forest. We use the algorithm to calculate a similarity…