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Title: Machine Learning for Massive Scale Cosmology. Final Report

Abstract

This report summarizes work done on applying machine learning algorithms in the domain of cosmology.

Authors:
 [1]
  1. Carnegie Mellon Univ., Pittsburgh, PA (United States)
Publication Date:
Research Org.:
Carnegie Mellon Univ., Pittsburgh, PA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
OSTI Identifier:
1355867
Report Number(s):
DOE-CMU-0002607
DOE Contract Number:  
SC0002607
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; Machine Learning Cosmology

Citation Formats

Schneider, Jeff. Machine Learning for Massive Scale Cosmology. Final Report. United States: N. p., 2017. Web. doi:10.2172/1355867.
Schneider, Jeff. Machine Learning for Massive Scale Cosmology. Final Report. United States. doi:10.2172/1355867.
Schneider, Jeff. Mon . "Machine Learning for Massive Scale Cosmology. Final Report". United States. doi:10.2172/1355867. https://www.osti.gov/servlets/purl/1355867.
@article{osti_1355867,
title = {Machine Learning for Massive Scale Cosmology. Final Report},
author = {Schneider, Jeff},
abstractNote = {This report summarizes work done on applying machine learning algorithms in the domain of cosmology.},
doi = {10.2172/1355867},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon May 08 00:00:00 EDT 2017},
month = {Mon May 08 00:00:00 EDT 2017}
}

Technical Report:

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