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Model-Constrained Deep Learning Approaches for Inverse Problems.

, и . CoRR, (2021)

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Bui-Quang-Thanh

Thanh Phong Bui

Thanh Huong Bui

Tân-Thanh Chu

Thanh Tan Mai

 

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iHDG: An Iterative HDG Framework for Partial Differential Equations., , и . SIAM J. Sci. Comput., (2017)Model-Constrained Deep Learning Approaches for Inverse Problems., и . CoRR, (2021)Accelerating PDE-constrained Inverse Solutions with Deep Learning and Reduced Order Models., , , , и . CoRR, (2019)Hierarchical Matrix Approximations of Hessians Arising in Inverse Problems Governed by PDEs., , , , , , , и . CoRR, (2020)Solving Bayesian Inverse Problems via Variational Autoencoders., , , и . MSML, том 145 из Proceedings of Machine Learning Research, стр. 386-425. PMLR, (2021)An improved iterative HDG approach for partial differential equations., , и . J. Comput. Phys., (2018)IMEX HDG-DG: a coupled implicit hybridized discontinuous Galerkin (HDG) and explicit discontinuous Galerkin (DG) approach for shallow water systems., , и . CoRR, (2017)eHDG: An Exponentially Convergent Iterative Solver for HDG Discretizations of Hyperbolic Partial Differential Equations., , и . CoRR, (2016)A Unified Discontinuous Petrov-Galerkin Method and Its Analysis for Friedrichs' Systems., , и . SIAM J. Numer. Anal., 51 (4): 1933-1958 (2013)A Randomized Maximum A Posteriori Method for Posterior Sampling of High Dimensional Nonlinear Bayesian Inverse Problems., , и . SIAM J. Sci. Comput., (2018)