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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)Probabilistic Density Function Method for Stochastic ODEs of Power Systems with Uncertain Power Input.P. Wang, D. Barajas-Solano, E. Constantinescu, S. Abhyankar, D. Ghosh, B. Smith, Z. Huang, and A. Tartakovsky. SIAM/ASA J. Uncertain. Quantification, 3 (1): 873-896 (2015)Learning Coarse-Grained Potentials for Binary Fluids.P. Gao, X. Yang, and A. Tartakovsky. J. Chem. Inf. Model., 60 (8): 3731-3745 (2020)Physics-informed Machine Learning Method for Forecasting and Uncertainty Quantification of Partially Observed and Unobserved States in Power Grids.A. Tartakovsky, and R. Tipireddy. HICSS, page 1-7. ScholarSpace, (2019)Exact PDF equations and closure approximations for advective-reactive transport.D. Venturi, D. Tartakovsky, A. Tartakovsky, and G. Karniadakis. J. Comput. Phys., (2013)Modeling electrokinetic flows by consistent implicit incompressible smoothed particle hydrodynamics.W. Pan, K. Kim, M. Perego, A. Tartakovsky, and M. Parks. J. Comput. Phys., (2017)Conditional Karhunen-Loève expansion for uncertainty quantification and active learning in partial differential equation models.R. Tipireddy, D. Barajas-Solano, and A. Tartakovsky. J. Comput. Phys., (2020)Physics-constrained deep neural network method for estimating parameters in a redox flow battery.Q. He, P. Stinis, and A. Tartakovsky. CoRR, (2021)Probability and Cumulative Density Function Methods for the Stochastic Advection-Reaction Equation.D. Barajas-Solano, and A. Tartakovsky. SIAM/ASA J. Uncertain. Quantification, 6 (1): 180-212 (2018)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)

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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.