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Title: Large-scale inverse model analyses employing fast randomized data reduction

ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [1]; ORCiD logo [1];  [2]
  1. Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos New Mexico USA
  2. Institute for Computational Sciences and Engineering, University of Texas at Austin, Austin Texas USA
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Sponsoring Org.:
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Journal Article: Publisher's Accepted Manuscript
Journal Name:
Water Resources Research
Additional Journal Information:
Related Information: CHORUS Timestamp: 2017-10-23 18:12:57; Journal ID: ISSN 0043-1397
American Geophysical Union (AGU)
Country of Publication:
United States

Citation Formats

Lin, Youzuo, Le, Ellen B., O'Malley, Daniel, Vesselinov, Velimir V., and Bui-Thanh, Tan. Large-scale inverse model analyses employing fast randomized data reduction. United States: N. p., 2017. Web. doi:10.1002/2016WR020299.
Lin, Youzuo, Le, Ellen B., O'Malley, Daniel, Vesselinov, Velimir V., & Bui-Thanh, Tan. Large-scale inverse model analyses employing fast randomized data reduction. United States. doi:10.1002/2016WR020299.
Lin, Youzuo, Le, Ellen B., O'Malley, Daniel, Vesselinov, Velimir V., and Bui-Thanh, Tan. 2017. "Large-scale inverse model analyses employing fast randomized data reduction". United States. doi:10.1002/2016WR020299.
title = {Large-scale inverse model analyses employing fast randomized data reduction},
author = {Lin, Youzuo and Le, Ellen B. and O'Malley, Daniel and Vesselinov, Velimir V. and Bui-Thanh, Tan},
abstractNote = {},
doi = {10.1002/2016WR020299},
journal = {Water Resources Research},
number = ,
volume = ,
place = {United States},
year = 2017,
month = 7

Journal Article:
Free Publicly Available Full Text
This content will become publicly available on August 12, 2018
Publisher's Accepted Manuscript

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