Goal-oriented, model-constrained optimization for reduction of large-scale systems. - Tan Bui-Thanh; Karen Willcox; Omar Ghattas; Bart G. van Bloemen Waanders (J. Comput. Phys., 2007)

Model Reduction for Large-Scale Systems with High-Dimensional Parametric Input Space. - Tan Bui-Thanh; Karen Willcox; Omar Ghattas (SIAM J. Sci. Comput., 2008)

Extreme-scale UQ for Bayesian inverse problems governed by PDEs. - Tan Bui-Thanh; Carsten Burstedde; Omar Ghattas; James Martin; Georg Stadler; Lucas C. Wilcox (SC, 2012)

Analysis of an hp-Nonconforming Discontinuous Galerkin Spectral Element Method for Wave Propagation. - Tan Bui-Thanh; Omar Ghattas (SIAM J. Numer. Anal., 2012)

Adaptive Hessian-Based Nonstationary Gaussian Process Response Surface Method for Probability Density Approximation with Application to Bayesian Solution of Large-Scale Inverse Problems. - Tan Bui-Thanh; Omar Ghattas; David Higdon (SIAM J. Sci. Comput., 2012)

Constructively well-posed approximation methods with unity inf-sup and continuity constants for partial differential equations. - Tan Bui-Thanh; Leszek F. Demkowicz; Omar Ghattas (Math. Comput., 2013)

A Unified Discontinuous Petrov-Galerkin Method and Its Analysis for Friedrichs' Systems. - Tan Bui-Thanh; Leszek F. Demkowicz; Omar Ghattas (SIAM J. Numer. Anal., 2013)

A Computational Framework for Infinite-Dimensional Bayesian Inverse Problems Part I: The Linearized Case, with Application to Global Seismic Inversion. - Tan Bui-Thanh; Omar Ghattas; James Martin; Georg Stadler (SIAM J. Sci. Comput., 2013)

A robust DPG method for convection-dominated diffusion problems II: Adjoint boundary conditions and mesh-dependent test norms. - Jesse Chan; Norbert Heuer; Tan Bui-Thanh; Leszek F. Demkowicz (Comput. Math. Appl., 2014)

The DPG method for the Stokes problem. - Nathan V. Roberts; Tan Bui-Thanh; Leszek F. Demkowicz (Comput. Math. Appl., 2014)

An Analysis of Infinite Dimensional Bayesian Inverse Shape Acoustic Scattering and Its Numerical Approximation. - Tan Bui-Thanh; Omar Ghattas (SIAM/ASA J. Uncertain. Quantification, 2014)

From Godunov to a unified hybridized discontinuous Galerkin framework for partial differential equations. - Tan Bui-Thanh (J. Comput. Phys., 2015)

Discretely Exact Derivatives for Hyperbolic PDE-Constrained Optimization Problems Discretized by the Discontinuous Galerkin Method. - Lucas C. Wilcox; Georg Stadler; Tan Bui-Thanh; Omar Ghattas (J. Sci. Comput., 2015)

A Randomized Misfit Approach for Data Reduction in Large-Scale Inverse Problems. - Ellen B. Le; Aaron Myers; Tan Bui-Thanh (CoRR, 2016)

eHDG: An Exponentially Convergent Iterative Solver for HDG Discretizations of Hyperbolic Partial Differential Equations. - Sriramkrishnan Muralikrishnan; Minh-Binh Tran; Tan Bui-Thanh (CoRR, 2016)

Emulation of higher-order tensors in manifold Monte Carlo methods for Bayesian Inverse Problems. - Shiwei Lan; Tan Bui-Thanh; Mike Christie; Mark A. Girolami (J. Comput. Phys., 2016)

Construction and Analysis of HDG Methods for Linearized Shallow Water Equations. - Tan Bui-Thanh (SIAM J. Sci. Comput., 2016)

Accelerating Markov Chain Monte Carlo with Active Subspaces. - Paul G. Constantine; Carson Kent; Tan Bui-Thanh (SIAM J. Sci. Comput., 2016)

IMEX HDG-DG: a coupled implicit hybridized discontinuous Galerkin (HDG) and explicit discontinuous Galerkin (DG) approach for shallow water systems. - Shinhoo Kang; Francis X. Giraldo; Tan Bui-Thanh (CoRR, 2017)

A Data Scalable Augmented Lagrangian KKT Preconditioner for Large-Scale Inverse Problems. - Nick Alger; Umberto Villa; Tan Bui-Thanh; Omar Ghattas (SIAM J. Sci. Comput., 2017)

iHDG: An Iterative HDG Framework for Partial Differential Equations. - Sriramkrishnan Muralikrishnan; Minh-Binh Tran; Tan Bui-Thanh (SIAM J. Sci. Comput., 2017)

A Hybridized Discontinuous Galerkin Method for A Linear Degenerate Elliptic Equation Arising from Two-Phase Mixtures. - Shinhoo Kang; Tan Bui-Thanh; Todd Arbogast (CoRR, 2018)

An improved iterative HDG approach for partial differential equations. - Sriramkrishnan Muralikrishnan; Minh-Binh Tran; Tan Bui-Thanh (J. Comput. Phys., 2018)

A Randomized Maximum A Posteriori Method for Posterior Sampling of High Dimensional Nonlinear Bayesian Inverse Problems. - Kainan Wang; Tan Bui-Thanh; Omar Ghattas (SIAM J. Sci. Comput., 2018)

Solving Forward and Inverse Problems Using Autoencoders. - Hwan Goh; Sheroze Sheriffdeen; Tan Bui-Thanh (CoRR, 2019)

Accelerating PDE-constrained Inverse Solutions with Deep Learning and Reduced Order Models. - Sheroze Sheriffdeen; Jean C. Ragusa; Jim E. Morel; Marvin L. Adams; Tan Bui-Thanh (CoRR, 2019)

Analysis of an HDG Method for Linearized Incompressible Resistive MHD Equations. - Jeonghun J. Lee; Stephen Shannon; Tan Bui-Thanh; John N. Shadid (SIAM J. Numer. Anal., 2019)

Scalable Matrix-Free Adaptive Product-Convolution Approximation for Locally Translation-Invariant Operators. - Nick Alger; Vishwas Rao; Aaron Myers; Tan Bui-Thanh; Omar Ghattas (SIAM J. Sci. Comput., 2019)

Unified Geometric Multigrid Algorithm for Hybridized High-Order Finite Element Methods. - Tim Wildey; Sriramkrishnan Muralikrishnan; Tan Bui-Thanh (SIAM J. Sci. Comput., 2019)

Hierarchical Matrix Approximations of Hessians Arising in Inverse Problems Governed by PDEs. - Ilona Ambartsumyan; Wajih Bou Karam; Tan Bui-Thanh; Omar Ghattas; David E. Keyes; Georg Stadler; George Turkiyyah; Stefano Zampini (CoRR, 2020)

A scalable exponential-DG approach for nonlinear conservation laws: with application to Burger and Euler equations. - Shinhoo Kang; Tan Bui-Thanh (CoRR, 2020)

A Multilevel Block Preconditioner for the HDG Trace System Applied to Incompressible Resistive MHD. - Sriramkrishnan Muralikrishnan; Stephen Shannon; Tan Bui-Thanh; John N. Shadid (CoRR, 2020)

IMEX HDG-DG: A coupled implicit hybridized discontinuous Galerkin and explicit discontinuous Galerkin approach for shallow water systems. - Shinhoo Kang; Francis X. Giraldo; Tan Bui-Thanh (J. Comput. Phys., 2020)

A multilevel approach for trace system in HDG discretizations. - Sriramkrishnan Muralikrishnan; Tan Bui-Thanh; John N. Shadid (J. Comput. Phys., 2020)

Hierarchical Matrix Approximations of Hessians Arising in Inverse Problems Governed by PDEs. - Ilona Ambartsumyan; Wajih Halim Boukaram; Tan Bui-Thanh; Omar Ghattas; David E. Keyes; Georg Stadler; George Turkiyyah; Stefano Zampini (SIAM J. Sci. Comput., 2020)

High-Speed Simulation of the 3D Behavior of Myocardium Using a Neural Network PDE Approach. - Wenbo Zhang; David S. Li; Tan Bui-Thanh; Michael S. Sacks (FIMH, 2021)

Solving Bayesian Inverse Problems via Variational Autoencoders. - Hwan Goh; Sheroze Sheriffdeen; Jonathan Wittmer; Tan Bui-Thanh (MSML, 2021)

Bridging and Improving Theoretical and Computational Electric Impedance Tomography via Data Completion. - Tan Bui-Thanh; Qin Li 007; Leonardo Zepeda-Núñez (CoRR, 2021)

Model-Constrained Deep Learning Approaches for Inverse Problems. - Hai Van Nguyen; Tan Bui-Thanh (CoRR, 2021)

A Unified and Constructive Framework for the Universality of Neural Networks. - Tan Bui-Thanh (CoRR, 2021)

Sequential ensemble transform for Bayesian inverse problems. - Aaron Myers; Alexandre H. Thiéry; Kainan Wang; Tan Bui-Thanh (J. Comput. Phys., 2021)

Forward and inverse modeling of fault transmissibility in subsurface flows. - Jeonghun J. Lee; Tan Bui-Thanh; Umberto Villa; Omar Ghattas (Comput. Math. Appl., 2022)

DIAS: A Data-Informed Active Subspace Regularization Framework for Inverse Problems. - Hai Van Nguyen; Jonathan Wittmer; Tan Bui-Thanh (Comput., 2022)

Probabilistic Constrained Bayesion Inversion for Transpiration Cooling. - Ella Steins; Tan Bui-Thanh; Michael Herty; Siegfried Müller (CoRR, 2022)

A Model-Constrained Tangent Manifold Learning Approach for Dynamical Systems. - Hai Van Nguyen; Tan Bui-Thanh (CoRR, 2022)

Layerwise Sparsifying Training and Sequential Learning Strategy for Neural Architecture Adaptation. - C. G. Krishnanunni; Tan Bui-Thanh (CoRR, 2022)

Use of mobile phone sensing data to estimate residence and mobility times in urban patches during the COVID-19 epidemic: The case of the 2020 outbreak in Hermosillo, Mexico. - L. Leticia Ramírez-Ramírez; José A. Montoya; Jesús F. Espinoza; Chahak Mehta; Albert Orwa Akuno; Tan Bui-Thanh (CoRR, 2022)

Bridging and Improving Theoretical and Computational Electrical Impedance Tomography via Data Completion. - Tan Bui-Thanh; Qin Li 007; Leonardo Zepeda-Núñez (SIAM J. Sci. Comput., 2022)

On Unifying Randomized Methods For Inverse Problems. - Jonathan Wittmer; C. G. Krishnanunni; Hai Van Nguyen; Tan Bui-Thanh (CoRR, 2023)

Unified hp-HDG Frameworks for Friedrichs' PDE systems. - Jau-Uei Chen; Shinhoo Kang; Tan Bui-Thanh; John N. Shadid (CoRR, 2023)

An autoencoder compression approach for accelerating large-scale inverse problems. - Jonathan Wittmer; Jacob C. Badger; Hari Sundar; Tan Bui-Thanh (CoRR, 2023)

A Divergence-Free and H(div)-Conforming Embedded-Hybridized DG Method for the Incompressible Resistive MHD equations. - Jau-Uei Chen; Tamás L. Horváth; Tan Bui-Thanh (CoRR, 2023)

A model-constrained Discontinuous Galerkin Network (DGNet) for Compressible Euler Equations with Out-of-Distribution Generalization. - Hai Van Nguyen; Jau-Uei Chen; William Cole Nockolds; Wesley Lao; Tan Bui-Thanh (CoRR, 2024)

TAEN: A Model-Constrained Tikhonov Autoencoder Network for Forward and Inverse Problems. - Hai V. Nguyen; Tan Bui-Thanh; Clint Dawson 001 (CoRR, 2024)

A unified hp-HDG framework for Friedrichs' PDE systems. - Jau-Uei Chen; Shinhoo Kang; Tan Bui-Thanh; John N. Shadid (Comput. Math. Appl., 2024)

TNet: A Model-Constrained Tikhonov Network Approach for Inverse Problems. - Hai Van Nguyen; Tan Bui-Thanh (SIAM J. Sci. Comput., 2024)

A Constant Velocity Latent Dynamics Approach for Accelerating Simulation of Stiff Nonlinear Systems. - William Cole Nockolds; C. G. Krishnanunni; Tan Bui-Thanh (CoRR, 2025)

Topological derivative approach for deep neural network architecture adaptation. - C. G. Krishnanunni; Tan Bui-Thanh; Clint Dawson 001 (CoRR, 2025)