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ORCIDTeeratorn Kadeethum
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2020 – today
- 2024
[j6]Teeratorn Kadeethum
, Christine Downs:
Harnessing Machine Learning and Data Fusion for Accurate Undocumented Well Identification in Satellite Images. Remote. Sens. 16(12): 2116 (2024)- 2023
- [j5]Teeratorn Kadeethum, John D. Jakeman, Youngsoo Choi, Nikolaos Bouklas, Hongkyu Yoon:
Epistemic Uncertainty-Aware Barlow Twins Reduced Order Modeling for Nonlinear Contact Problems. IEEE Access 11: 62970-62985 (2023) - [i14]Siu Wun Cheung, Youngsoo Choi, H. Keo Springer, Teeratorn Kadeethum:
Data-scarce surrogate modeling of shock-induced pore collapse process. CoRR abs/2306.00184 (2023) - [i13]Teeratorn Kadeethum, Daniel O'Malley, Youngsoo Choi, Hari S. Viswanathan, Hongkyu Yoon:
Progressive reduced order modeling: empowering data-driven modeling with selective knowledge transfer. CoRR abs/2310.03770 (2023) - [i12]Teeratorn Kadeethum, Stephen J. Verzi, Hongkyu Yoon:
Efficient machine-learning surrogates for large-scale geological carbon and energy storage. CoRR abs/2310.07461 (2023) - 2022
- [j4]Teeratorn Kadeethum, Daniel O'Malley, Youngsoo Choi, Hari S. Viswanathan, Nikolaos Bouklas, Hongkyu Yoon:
Continuous conditional generative adversarial networks for data-driven solutions of poroelasticity with heterogeneous material properties. Comput. Geosci. 167: 105212 (2022) - [i11]Teeratorn Kadeethum, Francesco Ballarin, Daniel O'Malley, Youngsoo Choi, Nikolaos Bouklas, Hongkyu Yoon:
Reduced order modeling with Barlow Twins self-supervised learning: Navigating the space between linear and nonlinear solution manifolds. CoRR abs/2202.05460 (2022) - [i10]Jan Niklas Fuhg, Arnav Karmarkar, Teeratorn Kadeethum, Hongkyu Yoon, Nikolaos Bouklas:
Deep Convolutional Ritz Method: Parametric PDE surrogates without labeled data. CoRR abs/2206.04675 (2022) - 2021
- [j3]Teeratorn Kadeethum, Sanghyun Lee, Francesco Ballarin, Jinhyun Choo, Hamidreza M. Nick:
A locally conservative mixed finite element framework for coupled hydro-mechanical-chemical processes in heterogeneous porous media. Comput. Geosci. 152: 104774 (2021) - [j2]Teeratorn Kadeethum, Hamidreza M. Nick, Sanghyun Lee, Francesco Ballarin:
Enriched Galerkin discretization for modeling poroelasticity and permeability alteration in heterogeneous porous media. J. Comput. Phys. 427: 110030 (2021) - [j1]Teeratorn Kadeethum, Daniel O'Malley, Jan Niklas Fuhg, Youngsoo Choi, Jonghyun Lee, Hari S. Viswanathan, Nikolaos Bouklas:
A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks. Nat. Comput. Sci. 1(12): 819-829 (2021) - [c1]Sanghyun Lee, Teeratorn Kadeethum:
Physics-informed Neural Networks for Solving Coupled Flow and Transport System. AAAI Spring Symposium: MLPS 2021 - [i9]Teeratorn Kadeethum, Francesco Ballarin, Nikolaos Bouklas:
Non-intrusive reduced order modeling of poroelasticity of heterogeneous media based on a discontinuous Galerkin approximation. CoRR abs/2101.11810 (2021) - [i8]Teeratorn Kadeethum, Daniel O'Malley, Jan Niklas Fuhg, Youngsoo Choi, Jonghyun Lee, Hari S. Viswanathan, Nikolaos Bouklas:
A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks. CoRR abs/2105.13136 (2021) - [i7]Teeratorn Kadeethum, Francesco Ballarin, Youngsoo Choi, Daniel O'Malley, Hongkyu Yoon, Nikolaos Bouklas:
Non-intrusive reduced order modeling of natural convection in porous media using convolutional autoencoders: comparison with linear subspace techniques. CoRR abs/2107.11460 (2021) - [i6]Teeratorn Kadeethum, Dan O'Malley, Youngsoo Choi, Hari S. Viswanathan, Nikolaos Bouklas, Hongkyu Yoon:
Continuous conditional generative adversarial networks for data-driven solutions of poroelasticity with heterogeneous material properties. CoRR abs/2111.14984 (2021) - 2020
- [i5]Teeratorn Kadeethum, Thomas M. Jørgensen, Hamidreza M. Nick:
Physics-informed Neural Networks for Solving Nonlinear Diffusivity and Biot's equations. CoRR abs/2002.08235 (2020) - [i4]Teeratorn Kadeethum, Thomas M. Jørgensen, Hamidreza M. Nick:
Physics-informed Neural Networks for Solving Inverse Problems of Nonlinear Biot's Equations: Batch Training. CoRR abs/2005.09638 (2020) - [i3]Sanghyun Lee, Teeratorn Kadeethum, Hamidreza M. Nick:
Choice of Interior Penalty Coefficient for Interior Penalty Discontinuous Galerkin Method for Biot's System by Employing Machine Learning. CoRR abs/2007.10119 (2020) - [i2]Teeratorn Kadeethum, Sanghyun Lee, Francesco Ballarin, Jinhyun Choo, Hamidreza M. Nick:
A Locally Conservative Mixed Finite Element Framework for Coupled Hydro-Mechanical-Chemical Processes in Heterogeneous Porous Media. CoRR abs/2010.04994 (2020) - [i1]Teeratorn Kadeethum, Hamidreza M. Nick, Sanghyun Lee, Francesco Ballarin:
Enriched Galerkin Discretization for Modeling Poroelasticity and Permeability Alteration in Heterogeneous Porous Media. CoRR abs/2010.06653 (2020)
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