Search Results for author: Alex I. Malz

Found 4 papers, 3 papers with code

How not to obtain the redshift distribution from probabilistic redshift estimates: Under what conditions is it not inappropriate to estimate the redshift distribution N(z) by stacking photo-z PDFs?

no code implementations12 Jan 2021 Alex I. Malz

In response, mathematically self-consistent models of varying complexity have been proposed in an effort to answer the question, "What is the right way to obtain the redshift distribution function $\mathcal{N}(z)$ from a catalog of photo-$z$ PDFs?"

Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics

Active learning with RESSPECT: Resource allocation for extragalactic astronomical transients

1 code implementation12 Oct 2020 Noble Kennamer, Emille E. O. Ishida, Santiago Gonzalez-Gaitan, Rafael S. de Souza, Alexander Ihler, Kara Ponder, Ricardo Vilalta, Anais Moller, David O. Jones, Mi Dai, Alberto Krone-Martins, Bruno Quint, Sreevarsha Sreejith, Alex I. Malz, Lluis Galbany

The Recommendation System for Spectroscopic follow-up (RESSPECT) project aims to enable the construction of optimized training samples for the Rubin Observatory Legacy Survey of Space and Time (LSST), taking into account a realistic description of the astronomical data environment.

Active Learning Astronomy +1

Conditional Density Estimation Tools in Python and R with Applications to Photometric Redshifts and Likelihood-Free Cosmological Inference

5 code implementations30 Aug 2019 Niccolò Dalmasso, Taylor Pospisil, Ann B. Lee, Rafael Izbicki, Peter E. Freeman, Alex I. Malz

We provide sample code in $\texttt{Python}$ and $\texttt{R}$ as well as examples of applications to photometric redshift estimation and likelihood-free cosmological inference via CDE.

Astronomy Density Estimation +2

The Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC): Data set

3 code implementations28 Sep 2018 The PLAsTiCC team, Tarek Allam Jr., Anita Bahmanyar, Rahul Biswas, Mi Dai, Lluís Galbany, Renée Hložek, Emille E. O. Ishida, Saurabh W. Jha, David O. Jones, Richard Kessler, Michelle Lochner, Ashish A. Mahabal, Alex I. Malz, Kaisey S. Mandel, Juan Rafael Martínez-Galarza, Jason D. McEwen, Daniel Muthukrishna, Gautham Narayan, Hiranya Peiris, Christina M. Peters, Kara Ponder, Christian N. Setzer, The LSST Dark Energy Science Collaboration, The LSST Transients, Variable Stars Science Collaboration

The Photometric LSST Astronomical Time Series Classification Challenge (PLAsTiCC) is an open data challenge to classify simulated astronomical time-series data in preparation for observations from the Large Synoptic Survey Telescope (LSST), which will achieve first light in 2019 and commence its 10-year main survey in 2022.

Instrumentation and Methods for Astrophysics Solar and Stellar Astrophysics

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