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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)

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The future low-temperature geochemical data-scape as envisioned by the U.S. geochemical community.S. Brantley, T. Wen, D. Agarwal, J. Catalano, P. Schroeder, K. Lehnert, C. Varadharajan, J. Pett-Ridge, M. Engle, A. Castronova and 10 other author(s). Comput. Geosci., (2021)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)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)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)BASIN-3D: A brokering framework to integrate diverse environmental data.C. Varadharajan, V. Hendrix, D. Christianson, M. Burrus, C. Wong, S. Hubbard, and D. Agarwal. Comput. Geosci., (2022)Sample Identifiers and Metadata to Support Data Management and Reuse in Multidisciplinary Ecosystem Sciences.J. Damerow, C. Varadharajan, K. Boye, E. Brodie, M. Burrus, K. Chadwick, R. Crystal-Ornelas, H. Elbashandy, R. Alves, K. Ely and 16 other author(s). Data Sci. J., (2021)Time Series Predictions in Unmonitored Sites: A Survey of Machine Learning Techniques in Water Resources.J. Willard, C. Varadharajan, X. Jia, and V. Kumar. CoRR, (2023)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)Balancing the needs of consumers and producers for scientific data collections.D. Agarwal, J. Damerow, C. Varadharajan, D. Christianson, G. Pastorello, Y. Cheah, and L. Ramakrishnan. Ecol. Informatics, (2021)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)

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Long-term missing value imputation for time series data using deep neural networks.

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Long-term missing value imputation for time series data using deep neural networks.

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Long-term missing value imputation for time series data using deep neural networks.