Publications

William Cole Nockolds, Thomas A. Scott, Tan Bui-Thanh, Shatad Purohit, Sitaram Ramaswamy (2026). Uncertainty-Aware Model-Constrained Neural Digital Twins for Real-Time Forecast, Calibration, and Control of Aeroelastic Airfoils. Proceedings of the Annual Conference of the PHM Society, Volume 18, No. 1, September 2026.

C G Krishnanunni, Thomas Scott, Tan Bui-Thanh (2026). An optimal control approach for neural network architecture adaptation with a posteriori error estimation. arXiv preprint, Submitted, 2026.

Hoang Tran, Hao Li, Vinh Ngoc Tran, Tam V Nguyen, Manh-Hung Le, Thanh Duc Dang, Hong Xuan Do, Hung T. Pham, Tan Bui-Thanh, L. Ruby Leung (2026). Short-Term Hourly Weather Forecasting using PredRNN with Image Preprocessing. Journal of Geophysical Research - Machine Learning and Computation, Open Access July, 2026.

Thomas A. Scott, Lukas Taus, Yen-Hsi Richard Tsai, Tan Bui-Thanh, Justin G. R. Delva (2026). Rendezvous Planning from Sparse Observations of Optimally Controlled Targets. Proceedings of the 65th IEEE Conference on Decision and Control (CDC), accepted, July 2026.

Alois Duston, Tan Bui-Thanh (2026). Laplace-Fisher Gate Identities for Optimal Matrix-Gated Blended Score Estimation. Arxiv Manuscript, 2026.

Shinhoo Kang, Hai V. Nguyen, Tan Bui-Thanh (2026). Second-order consistency for learning chaotic dynamics via randomized Jacobian matching. arXiv preprint, Submitted, 2026.

William Cole Nockolds, C. G. Krishnanunni, Tan Bui-Thanh, Xianxhu Tang (2026). LiLaN: A Linear Latent Network as the Solution Operator for Real-Time Solutions to Stiff Nonlinear Ordinary Differential Equations. Machine Learning for Computational Science and Engineering, Volume 2, article number 19, May 2026.

Tan Bui-Thanh (2026). The AI Research Assistant: Promise, Peril, and a Proof of Concept. IEEE Computing in Science and Engineering, April, 2026.

Jamie Mahowald, Tan Bui-Thanh (2026). Generalization Limits of In-Context Operator Networks for Higher-Order Partial Differential Equations. SIAM Undergraduate Research Online, accepted, March 2026.

Tan Bui-Thanh, Giancarlo Villatoro, C. G. Krishnanunni (2026). From an Elementary Proof of Error Representation for Hermite Quadrature to a Rediscovery of Legendre Polynomials and Rodrigues Formula. SIURO, Submitted, 2026.

A. Tonini, Tan Bui-Thanh, F. Regazzoni, L. Dedè, A. Quarteroni (2026). Improvements on uncertainty quantification with variational autoencoders. Mathematical Models and Methods in Applied Sciences, 36(04), 787–823 February, 2026.

C G Krishnanunni, Jonathan Wittmer, Tan Bui-Thanh, Quoc P. Nguyen (2026). A New Look at the Ensemble Kalman Filter for Inverse Problems: Duality, Non-Asymptotic Analysis and Convergence Acceleration. Inverse Problems, Submitted, 2026.

Alois Duston, Tan Bui-Thanh (2026). Variance-Reduced Diffusion Sampling via Target Score Identity. SIAM SISC, Submitted, 2026.

C G Krishnanunni, Tan Bui-Thanh, Clint Dawson (2026). Topological derivative approach for deep neural network architecture adaptation. SIAM Journal on Scientific Computing, accepted, 2026.

Hai V. Nguyen, Tan Bui-Thanh, Clint Dawson (2025). TAEN: A Model-Constrained Tikhonov Autoencoder Network for Forward and Inverse Problems. Computer Methods in Applied Mechanics and Engineering, Volume 446, Part A, 1 November 2025, 118245, 2025.

C G Krishnanunni, Tan Bui-Thanh (2025). An Adaptive and Stability-Promoting Layerwise Training Approach for Sparse Deep Neural Network Architecture. Computer Methods in Applied Mechanics and Engineering, Volume 441, 1 June 2025, 117938, 2025.

Hai V. Nguyen, Jau-Uei Chen, Tan Bui-Thanh (2025). A Model-Constrained Discontinuous Galerkin Network (DGNet) for Compressible Euler Equations with Out-of-Distribution Generalization. Computer Methods in Applied Mechanics and Engineering, Volume 440, 15 May 2025, 117912, 2025.

L. Leticia Ramirez-Ramirez, José A. Montoya, Jesús F. Espinoza, Chahak Mehta, Albert Orwa Akuno, Tan Bui-Thanh (2025). Use of mobile phone sensing data to estimate residence and occupation times in urban patches: human mobility restrictions and the 2020 COVID-19 outbreak in Hermosillo, Mexico. Computational Urban Science, 5, article 10.

Jau-Uei Chen, Tamás L. Horváth, Tan Bui-Thanh (2024). A Divergence-Free and H(div)-Conforming Embedded-Hybridized DG Method for the Incompressible Resistive MHD equations. Computer Methods in Applied Mechanics and Engineering, 432, Part A, 117415.

Tri Pham, Quoc Nguyen (2024). Microseismic events based characterization of fractal fracture network. Fuels, 5(4), 839–856.

John Breedis, Tan Bui-Thanh (2024). Evaluating nAI and Quadrature Based Neural Networks. SIAM Undergraduate Research Online, Under Review, 2024.

Hai V. Nguyen, Tan Bui-Thanh (2024). TNet: A Model-Constrained Tikhonov Network Approach for Inverse Problems. SIAM Journal on Scientific Computing, 46(1), C77–C100.

Jau-Uei Chen, Shinhoo Kang, Tan Bui-Thanh, John Shadid (2024). Unified hp-HDG Frameworks for Friedrichs' PDE systems. Computers & Mathematics with Applications, Volume 154, Pages 236-266, 15 January 2024.

Tan Bui-Thanh (2024). Adjoint and Its roles in Sciences, Engineering, and Mathematics: A Tutorial. SIAM book in progress, 2024.

Russell Philley, Hai V. Nguyen, Tan Bui-Thanh (2023). Model-constrained uncertainty quantification for scientific deep learning of inverse solutions. the XLIV Iberto-Latin American Congress on Computational Mechanics in Engineering, Refereed proceeding, November, 2023.

T. Bui-Thanh (2023). A Unified and Constructive Framework for the Universality of Neural Networks. The IMA Journal of Applied Mathematics, hxad032, November, 2023.

Jonathan Wittmer, Jacob Badger, Hari Sundar, Tan Bui-Thanh (2023). An autoencoder compression approach for accelerating large-scale inverse problems. Inverse Problems, 39, 115009.

Albert Orwa Akuno, L. Leticia Ramirez-Ramirez, Chahak Mehta, T. Bui-Thanh, Jose Arturo Montoya (2023). Multi-patch epidemic models with partial mobility, residency, and demography. Chaos, Solitons & Fractals, Volume 173, August, 113690, 2023.

Jonathan Wittmer, Krishnanunni C.G., Hai V. Nguyen (2023). On Unifying Randomized Methods for Inverse Problems. Inverse Problems, Volume 39, Number 7, 075010, June, 2023.

Hai V. Nguyen, Tan Bui-Thanh (2023). A Model-Constrained Tangent Slope Learning Approach for Dynamical Systems. International Journal of Computational Fluid Dynamics, 36(7), 655-685, February 10, 2023.

Sriramkrishnan Muralikrishnan, Stephen Shannon, Tan Bui-Thanh, John N. Shadid (2023). A Multilevel Block Preconditioner for the HDG Trace System Applied to Incompressible Resistive MHD. Computer Methods in Applied Mechanics and Engineering, 401, 115775, February 1, 2023.

Ella Steins, Tan Bui-Thanh, Michael Herty, Siegfried Muller (2022). Probabilistic Constrained Bayesian Inversion for Transpiration Cooling. International Journal for Numerical Methods in Fluids, 94(12), 2020–2039.

Hwan Goh, Sheroze Sheriffdeen, Jonathan Wittmer, Tan Bui-Thanh (2022). Solving Bayesian Inverse Problems via Variational Autoencoders. Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145, 386–425.

Wenbo Zhang, David S. Li, Tan Bui-Thanh, Michael S. Sacks (2022). Simulation of the 3D Hyperelastic Behavior of Ventricular Myocardium using a Finite-Element Based Neural-Network Approach. Computer Methods in Applied Mechanics and Engineering, Volume 394, 114871, 2022.

Hai Nguyen, Jonathan Wittmer, Tan Bui-Thanh (2022). DIAS: A Data-Informed Active Subspace regularization framework for inverse problems. MDPI Computation, 10 (38), https://doi.org/10.3390/computation10030038, 2022.

Tan Bui-Thanh, Qin Li, Leonardo Zepeda-Núñez (2022). Bridging and Improving Theoretical and Computational Electric Impedance Tomography via Data Completion. SIAM Journal on Scientific Computing, 44(3), B668-B693, 2022.

Shinhoo Kang, Tan Bui-Thanh (2021). A scalable exponential-DG approach for nonlinear conservation laws: with application to Burger and Euler equations. Computer Methods in Applied Mechanics and Engineering, Volume 385, 1 November 2021, 114031.

Wenbo Zhang, David S. Li, Tan Bui-Thanh, Michael S. Sacks (2021). High-Speed Simulation of the 3D Behavior of Myocardium Using a Neural Network PDE Approach. Functional Imaging and Modeling of the Heart, Lecture Notes in Computer Science, Issue 6, Editor: Ennis, Daniel B. and Perotti, Luigi E. and Wang, Vicky Y., page: 416–424, June, 2021.

Jonathan Wittmer, Tan Bui-Thanh (2021). Data-Informed Regularization For Inverse and Imaging Problems. Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging, 1–38.

Sriramkrishnan Muralikrishnan, Tan Bui-Thanh, John N. Shadid (2020). A Multilevel Approach for Trace System in HDG Discretizations. Journal of Computational Physics, 407, 109240, 2020.