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A metadata reporting framework (FRAMES) for synthesis of ecohydrological observations.

D. Christianson, C. Varadharajan, B. Christoffersen, M. Detto, B. Faybishenko, B. Gimenez, V. Hendrix, K. Jardine, R. Juárez, G. Pastorello, T. Powell, M. Sandesh, J. Warren, B. Wolfe, J. Chambers, L. Kueppers, N. McDowell, and D. Agarwal. Ecol. Informatics, (2017)

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Nuchim Borissowsky

Svetlana Borisova

Bettina Borisch

Klaus Borisch

Wilfried Borisch

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Assessing data change in scientific datasets.J. Müller, B. Faybishenko, D. Agarwal, S. Bailey, C. Jiang, Y. Ryu, C. Tull, and L. Ramakrishnan. Concurr. Comput. Pract. Exp., (2021)Observational Data Patterns for Time Series Data Quality Assessment.G. Pastorello, D. Agarwal, D. Papale, T. Samak, C. Trotta, A. Ribeca, C. Poindexter, B. Faybishenko, D. Gunter, R. Hollowgrass and 1 other author(s). eScience, page 271-278. IEEE Computer Society, (2014)A science data gateway for environmental management.D. Agarwal, B. Faybishenko, V. Freedman, H. Krishnan, G. Kushner, C. Lansing, E. Porter, A. Romosan, A. Shoshani, H. Wainwright and 2 other author(s). Concurr. Comput. Pract. Exp., 28 (7): 1994-2004 (2016)A metadata reporting framework (FRAMES) for synthesis of ecohydrological observations.D. Christianson, C. Varadharajan, B. Christoffersen, M. Detto, B. Faybishenko, B. Gimenez, V. Hendrix, K. Jardine, R. Juárez, G. Pastorello and 8 other author(s). Ecol. Informatics, (2017)Challenges in Building an End-to-End System for Acquisition, Management, and Integration of Diverse Data From Sensor Networks in Watersheds: Lessons From a Mountainous Community Observatory in East River, Colorado.C. Varadharajan, B. Faybishenko, A. Henderson, M. Henderson, V. Hendrix, S. Hubbard, Z. Kakalia, A. Newman, B. Potter, H. Steltzer and 12 other author(s). IEEE Access, (2019)Surrogate optimization of deep neural networks for groundwater predictions.J. Müller, J. Park, R. Sahu, C. Varadharajan, B. Arora, B. Faybishenko, and D. Agarwal. J. Glob. Optim., 81 (1): 203-231 (2021)Long-term missing value imputation for time series data using deep neural networks.J. Park, J. Müller, B. Arora, B. Faybishenko, G. Pastorello, C. Varadharajan, R. Sahu, and D. Agarwal. Neural Comput. Appl., 35 (12): 9071-9091 (April 2023)Surrogate Optimization of Deep Neural Networks for Groundwater Predictions.J. Müller, J. Park, R. Sahu, C. Varadharajan, B. Arora, B. Faybishenko, and D. Agarwal. CoRR, (2019)Hunting Data Rogues at Scale: Data Quality Control for Observational Data in Research Infrastructures.G. Pastorello, D. Gunter, H. Chu, D. Christianson, C. Trotta, E. Canfora, B. Faybishenko, Y. Cheah, N. Beekwilder, S. Chan and 8 other author(s). eScience, page 446-447. IEEE Computer Society, (2017)Long-Term Missing Value Imputation for Time Series Data Using Deep Neural Networks.J. Park, J. Müller, B. Arora, B. Faybishenko, G. Pastorello, C. Varadharajan, R. Sahu, and D. Agarwal. CoRR, (2022)

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Disambiguation of "Faybishenko, Boris"

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A metadata reporting framework (FRAMES) for synthesis of ecohydrological observations.

Please choose a person to relate this publication to

Nuchim Borissowsky

Svetlana Borisova

Bettina Borisch

Klaus Borisch

Wilfried Borisch

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Faybishenko, Boris"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML A metadata reporting framework (FRAMES) for synthesis of ecohydrological observations.

Please choose a person to relate this publication to

Nuchim Borissowsky

Svetlana Borisova

Bettina Borisch

Klaus Borisch

Wilfried Borisch

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
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APA
Chicago
DIN 1505
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MSOffice XML

A metadata reporting framework (FRAMES) for synthesis of ecohydrological observations.