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Differentiable modeling to unify machine learning and physical models and advance Geosciences.

C. Shen, A. Appling, P. Gentine, T. Bandai, H. Gupta, A. Tartakovsky, M. Baity-Jesi, F. Fenicia, D. Kifer, L. Li, X. Liu, W. Ren, Y. Zheng, C. Harman, M. Clark, M. Farthing, D. Feng, P. Kumar, D. Aboelyazeed, F. Rahmani, H. Beck, T. Bindas, D. Dwivedi, K. Fang, M. Höge, C. Rackauckas, T. Roy, C. Xu, and K. Lawson. CoRR, (2023)

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Alexandre Darmoise

Alexandre Varnek

Alexandre Martins

Alexandre Alexeev

Alexandre Nekrassov

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Differentiable modeling to unify machine learning and physical models and advance Geosciences.C. Shen, A. Appling, P. Gentine, T. Bandai, H. Gupta, A. Tartakovsky, M. Baity-Jesi, F. Fenicia, D. Kifer, L. Li and 19 other author(s). CoRR, (2023)Electric Load and Power Forecasting Using Ensemble Gaussian Process Regression.T. Ma, R. Huang, D. Barajas-Solano, R. Tipireddy, and A. Tartakovsky. CoRR, (2019)Physics-Informed Kriging: A Physics-Informed Gaussian Process Regression Method for Data-Model Convergence.X. Yang, G. Tartakovsky, and A. Tartakovsky. CoRR, (2018)Stochastically Forced Ensemble Dynamic Mode Decomposition for Forecasting and Analysis of Near-Periodic Systems.D. Dylewsky, D. Barajas-Solano, T. Ma, A. Tartakovsky, and J. Kutz. IEEE Access, (2022)Discrete Models of Fluids: Spatial Averaging, Closure, and Model Reduction.A. Panchenko, A. Tartakovsky, and K. Cooper. SIAM J. Appl. Math., 74 (2): 477-515 (2014)Physics-Informed Gaussian Process Regression for Probabilistic States Estimation and Forecasting in Power Grids.T. Ma, D. Barajas-Solano, R. Tipireddy, and A. Tartakovsky. CoRR, (2020)Physics-informed CoKriging model of a redox flow battery.A. Howard, and A. Tartakovsky. CoRR, (2021)Time-dependent stochastic basis adaptation for uncertainty quantification.R. Tipireddy, P. Stinis, and A. Tartakovsky. CoRR, (2021)Physics-Informed Neural Network Method for Parabolic Differential Equations with Sharply Perturbed Initial Conditions.Y. Zong, Q. He, and A. Tartakovsky. CoRR, (2022)Enforcing constraints for interpolation and extrapolation in Generative Adversarial Networks.P. Stinis, T. Hagge, A. Tartakovsky, and E. Yeung. CoRR, (2018)

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Disambiguation of "Tartakovsky, Alexandre"

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Differentiable modeling to unify machine learning and physical models and advance Geosciences.

Please choose a person to relate this publication to

Alexandre Darmoise

Alexandre Varnek

Alexandre Martins

Alexandre Alexeev

Alexandre Nekrassov

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Tartakovsky, Alexandre"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Differentiable modeling to unify machine learning and physical models and advance Geosciences.

Please choose a person to relate this publication to

Alexandre Darmoise

Alexandre Varnek

Alexandre Martins

Alexandre Alexeev

Alexandre Nekrassov

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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history of this post
URL
DOI
BibTeX
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APA
Chicago
DIN 1505
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Differentiable modeling to unify machine learning and physical models and advance Geosciences.