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Model-Constrained Deep Learning Approaches for Inverse Problems., and . CoRR, (2021)Accelerating PDE-constrained Inverse Solutions with Deep Learning and Reduced Order Models., , , , and . CoRR, (2019)Hierarchical Matrix Approximations of Hessians Arising in Inverse Problems Governed by PDEs., , , , , , , and . CoRR, (2020)iHDG: An Iterative HDG Framework for Partial Differential Equations., , and . SIAM J. Sci. Comput., (2017)Solving Bayesian Inverse Problems via Variational Autoencoders., , , and . MSML, volume 145 of Proceedings of Machine Learning Research, page 386-425. PMLR, (2021)An improved iterative HDG approach for partial differential equations., , and . J. Comput. Phys., (2018)An Analysis of Infinite Dimensional Bayesian Inverse Shape Acoustic Scattering and Its Numerical Approximation., and . SIAM/ASA J. Uncertain. Quantification, 2 (1): 203-222 (2014)A Divergence-Free and H(div)-Conforming Embedded-Hybridized DG Method for the Incompressible Resistive MHD equations., , and . CoRR, (2023)Solving Forward and Inverse Problems Using Autoencoders., , and . CoRR, (2019)A Randomized Misfit Approach for Data Reduction in Large-Scale Inverse Problems., , and . CoRR, (2016)