Hongkyu Yoon

Technical Staff, Sandia National Laboratories

Joined

May 2022

Names

Hongkyu Yoon (Preferred)

Emails

****@sandia.gov (Confirmed)

Personal Links

Google Scholar

DBLP

Career & Education History

Technical Staff

Sandia National Laboratories (sandia.gov)

2014 – Present

Postdoc

Sandia National Laboratories (sandia.gov)

2010 – 2013

Principal Researcher

University of Illinois at Urbana-Champaign (uiuc.edu)

2006 – 2010

Advisors, Relations & Conflicts

No relations added

Expertise

VAEs

WGAN for Data assimilation

2020 – Present

GANs

Image segmentation

satellite images

2019 – Present

Deep learning

Physics informed machine learning

2016 – Present

Publications

Estimation of Physical Coefficients for CO$_2$ Sequestration using Deep Generative Priors based Inverse Modeling Framework
Jiawei Shen, Jonghyun Lee, Hongkyu Yoon
- SynS & ML @ ICML2023
- Readers: Everyone
Coupling Self-Attention Generative Adversarial Network and Bayesian Inversion for Carbon Storage System
Jichao Bao, Jonghyun Lee, Hongkyu Yoon
- SynS & ML @ ICML2023
- Readers: Everyone
Epistemic Uncertainty-Aware Barlow Twins Reduced Order Modeling for Nonlinear Contact Problems
Teeratorn Kadeethum, John D. Jakeman, Youngsoo Choi, Nikolaos Bouklas, Hongkyu Yoon
- Published: 01 Jan 2023, Last Modified: 05 Nov 2023
- IEEE Access 2023
- Readers: Everyone
Subsurface Characterization using Ensemble-based Approaches with Deep Generative Models
Jichao Bao, Hongkyu Yoon, Jonghyun Lee
- Published: 01 Jan 2023, Last Modified: 05 Nov 2023
- CoRR 2023
- Readers: Everyone
Progressive reduced order modeling: empowering data-driven modeling with selective knowledge transfer
Teeratorn Kadeethum, Daniel O'Malley, Youngsoo Choi, Hari S. Viswanathan, Hongkyu Yoon
- Published: 01 Jan 2023, Last Modified: 05 Nov 2023
- CoRR 2023
- Readers: Everyone
Efficient machine-learning surrogates for large-scale geological carbon and energy storage
Teeratorn Kadeethum, Stephen J. Verzi, Hongkyu Yoon
- Published: 01 Jan 2023, Last Modified: 05 Nov 2023
- CoRR 2023
- Readers: Everyone
Machine Learning in Heterogeneous Porous Materials
Marta D'Elia, Hang Deng, Cedric G. Fraces, Krishna C. Garikipati, Lori Graham-Brady, Amanda A. Howard, George Em Karniadakis, Vahid Keshavarzzadeh, Robert M. Kirby, J. Nathan Kutz, Chunhui Li, Xing Liu, Hannah Lu, Pania Newell, Daniel O'Malley, Masa Prodanovic, Gowri Srinivasan, Alexandre M. Tartakovsky, Daniel M. Tartakovsky, Hamdi A. Tchelepi et al. (4 additional authors not shown)
- Published: 01 Jan 2022, Last Modified: 05 Nov 2023
- CoRR 2022
- Readers: Everyone
Continuous conditional generative adversarial networks for data-driven solutions of poroelasticity with heterogeneous material properties
Teeratorn Kadeethum, Daniel O'Malley, Youngsoo Choi, Hari S. Viswanathan, Nikolaos Bouklas, Hongkyu Yoon
- Published: 01 Jan 2022, Last Modified: 05 Nov 2023
- Comput. Geosci. 2022
- Readers: Everyone
Reduced order modeling with Barlow Twins self-supervised learning: Navigating the space between linear and nonlinear solution manifolds
Teeratorn Kadeethum, Francesco Ballarin, Daniel O'Malley, Youngsoo Choi, Nikolaos Bouklas, Hongkyu Yoon
- Published: 01 Jan 2022, Last Modified: 05 Nov 2023
- CoRR 2022
- Readers: Everyone
Deep Convolutional Ritz Method: Parametric PDE surrogates without labeled data
Jan Niklas Fuhg, Arnav Karmarkar, Teeratorn Kadeethum, Hongkyu Yoon, Nikolaos Bouklas
- Published: 01 Jan 2022, Last Modified: 05 Nov 2023
- CoRR 2022
- Readers: Everyone

View all 17 publications

Co-Authors

View all 42 co-authors