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Velimir V. Vesselinov

Los Alamos National Laboratory

172

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1728

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Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration and Development of Hidden Geothermal Resources

2021
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COVID-19: Spatiotemporal social data analytics and machine learning for pandemic exploration and forecasting

2021
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Transfer Operator Framework for Earth System Predictability and Water Cycle Extremes

2021
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Machine-Learning Predictions of the Shale Wells’ Performance

2021 Journal of Natural Gas Science and Engineering
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A comparative study of machine learning models for predicting the state of reactive mixing

2021 Journal of Computational Physics
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Characterizing Drought Behavior using Unsupervised Machine Learning for Improved Understanding of Future Drought in the Colorado River Basin

2021
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Discovering Hidden Geothermal Signatures using Unsupervised Machine Learning

2021
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Machine learning to identify geologic factors associated with production in geothermal fields: A casestudy using 3D geologic data, Brady geothermal field, Nevada

2021
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A Tectonic Shift in Analytics and Computing Is Coming

2021 Eos
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Augmenting geophysical interpretation of data-driven operational water supply forecast modeling for a western US river using a hybrid machine learning approach

2021 Journal of Hydrology
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