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2020 – today
- 2024
[j15]Jessica T. Lauzon
, Siu Wun Cheung, Yeonjong Shin, Youngsoo Choi, Dylan Matthew Copeland, Kevin Huynh:
S-OPT: A Points Selection Algorithm for Hyper-Reduction in Reduced Order Models. SIAM J. Sci. Comput. 46(4): 474- (2024)- [i41]Seung Whan Chung, Youngsoo Choi, Pratanu Roy, Thomas Moore, Thomas Roy, Tiras Y. Lin, Du Y. Nguyen, Christopher Hahn, Eric B. Duoss, Sarah E. Baker:
Train Small, Model Big: Scalable Physics Simulators via Reduced Order Modeling and Domain Decomposition. CoRR abs/2401.10245 (2024) - [i40]Jun Sur Richard Park, Siu Wun Cheung, Youngsoo Choi, Yeonjong Shin:
tLaSDI: Thermodynamics-informed latent space dynamics identification. CoRR abs/2403.05848 (2024) - [i39]Christophe Bonneville, Xiaolong He, April Tran, Jun Sur Richard Park, William Fries, Daniel A. Messenger, Siu Wun Cheung, Yeonjong Shin, David M. Bortz, Debojyoti Ghosh, Jiun-Shyan Chen, Jonathan L. Belof, Youngsoo Choi:
A Comprehensive Review of Latent Space Dynamics Identification Algorithms for Intrusive and Non-Intrusive Reduced-Order-Modeling. CoRR abs/2403.10748 (2024) - [i38]Xiaolong He, April Tran, David M. Bortz, Youngsoo Choi:
Physics-informed active learning with simultaneous weak-form latent space dynamics identification. CoRR abs/2407.00337 (2024) - [i37]Michael Juhasz, Eric B. Chin, Youngsoo Choi, Joseph T. McKeown, Saad A. Khairallah:
Data-driven Virtual Test-bed of the Blown Powder Directed Energy Deposition Process. CoRR abs/2409.09092 (2024) - [i36]Seung Whan Chung, Youngsoo Choi, Pratanu Roy, Thomas Roy, Tiras Y. Lin, Du T. Nguyen, Christopher Hahn, Eric B. Duoss, Sarah E. Baker:
Scaled-up prediction of steady Navier-Stokes equation with component reduced order modeling. CoRR abs/2410.21534 (2024) - [i35]Seung Whan Chung, Youngsoo Choi, Pratanu Roy, Thomas Roy, Tiras Y. Lin, Du T. Nguyen, Christopher Hahn, Eric B. Duoss, Sarah E. Baker:
Scalable physics-guided data-driven component model reduction for steady Navier-Stokes flow. CoRR abs/2410.21583 (2024) - 2023
- [j14]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) - [j13]Siu Wun Cheung, Youngsoo Choi, Dylan Matthew Copeland, Kevin Huynh:
Local Lagrangian reduced-order modeling for the Rayleigh-Taylor instability by solution manifold decomposition. J. Comput. Phys. 472: 111655 (2023) - [j12]Quincy A. Huhn, Mauricio E. Tano, Jean C. Ragusa, Youngsoo Choi:
Parametric dynamic mode decomposition for reduced order modeling. J. Comput. Phys. 475: 111852 (2023) - [j11]Xiaolong He, Youngsoo Choi, William D. Fries, Jonathan L. Belof, Jiun-Shyan Chen:
gLaSDI: Parametric physics-informed greedy latent space dynamics identification. J. Comput. Phys. 489: 112267 (2023) - [j10]Cosmin G. Petra, Miguel A. Salazar de Troya, Noemi Petra, Youngsoo Choi, Geoffrey M. Oxberry, Daniel A. Tortorelli:
On the implementation of a quasi-Newton interior-point method for PDE-constrained optimization using finite element discretizations. Optim. Methods Softw. 38(1): 59-90 (2023) - [c5]Youngsoo Choi, Yongmun Yun, Woo-Jeong Jeon, Seung-Hyun Kong:
A Novel Approach for Estimating Vehicle Speed in Nighttime Traffic Accidents from Daytime Video Information. ITSC 2023: 1368-1374 - [i34]Alejandro N. Diaz, Youngsoo Choi, Matthias Heinkenschloss:
A fast and accurate domain-decomposition nonlinear manifold reduced order model. CoRR abs/2305.15163 (2023) - [i33]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) - [i32]Christophe Bonneville, Youngsoo Choi, Debojyoti Ghosh, Jonathan L. Belof:
GPLaSDI: Gaussian Process-based Interpretable Latent Space Dynamics Identification through Deep Autoencoder. CoRR abs/2308.05882 (2023) - [i31]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) - [i30]Ping-Hsuan Tsai, Seung Whan Chung, Debojyoti Ghosh, John Loffeld, Youngsoo Choi, Jonathan L. Belof:
Accelerating Kinetic Simulations of Electrostatic Plasmas with Reduced-Order Modeling. CoRR abs/2310.18493 (2023) - [i29]April Tran, Xiaolong He, Daniel A. Messenger, Youngsoo Choi, David M. Bortz:
Weak-Form Latent Space Dynamics Identification. CoRR abs/2311.12880 (2023) - [i28]Tianshu Wen, Kookjin Lee, Youngsoo Choi:
Reduced-order modeling for parameterized PDEs via implicit neural representations. CoRR abs/2311.16410 (2023) - [i27]Aaron L. Brown, Eric B. Chin, Youngsoo Choi, Saad A. Khairallah, Joseph T. McKeown:
A Data-Driven, Non-Linear, Parameterized Reduced Order Model of Metal 3D Printing. CoRR abs/2311.18036 (2023) - [i26]Seung-Won Suh, Seung Whan Chung, Peer-Timo Bremer, Youngsoo Choi:
Accelerating Flow Simulations using Online Dynamic Mode Decomposition. CoRR abs/2311.18715 (2023) - [i25]Alejandro N. Diaz, Youngsoo Choi, Matthias Heinkenschloss:
Nonlinear-manifold reduced order models with domain decomposition. CoRR abs/2312.00713 (2023) - [i24]Christophe Bonneville, Youngsoo Choi, Debojyoti Ghosh, Jonathan L. Belof:
Data-Driven Autoencoder Numerical Solver with Uncertainty Quantification for Fast Physical Simulations. CoRR abs/2312.01021 (2023) - 2022
- [j9]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) - [j8]Youngkyu Kim, Youngsoo Choi, David P. Widemann, Tarek I. Zohdi:
A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder. J. Comput. Phys. 451: 110841 (2022) - [i23]Siu Wun Cheung, Youngsoo Choi, Dylan Matthew Copeland, Kevin Huynh:
Local Lagrangian reduced-order modeling for Rayleigh-Taylor instability by solution manifold decomposition. CoRR abs/2201.07335 (2022) - [i22]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) - [i21]William Fries, Xiaolong He, Youngsoo Choi:
LaSDI: Parametric Latent Space Dynamics Identification. CoRR abs/2203.02076 (2022) - [i20]Jessica T. Lauzon, Siu Wun Cheung, Yeonjong Shin, Youngsoo Choi, Dylan Matthew Copeland, Kevin Huynh:
S-OPT: A Points Selection Algorithm for Hyper-Reduction in Reduced Order Models. CoRR abs/2203.16494 (2022) - [i19]Xiaolong He, Youngsoo Choi, William D. Fries, Jon Belof, Jiun-Shyan Chen:
gLaSDI: Parametric Physics-informed Greedy Latent Space Dynamics Identification. CoRR abs/2204.12005 (2022) - [i18]Quincy A. Huhn, Mauricio E. Tano, Jean C. Ragusa, Youngsoo Choi:
Parametric Dynamic Mode Decomposition for Reduced Order Modeling. CoRR abs/2204.12006 (2022) - [i17]Sean McBane, Youngsoo Choi, Karen Willcox:
Stress-constrained topology optimization of lattice-like structures using component-wise reduced order models. CoRR abs/2205.09629 (2022) - [i16]Charles F. Jekel, Dane M. Sterbentz, Sylvie Aubry, Youngsoo Choi, Daniel A. White, Jonathan L. Belof:
Using Conservation Laws to Infer Deep Learning Model Accuracy of Richtmyer-Meshkov Instabilities. CoRR abs/2208.11477 (2022) - [i15]Xiaolong He, Youngsoo Choi, William D. Fries, Jonathan L. Belof, Jiun-Shyan Chen:
Certified data-driven physics-informed greedy auto-encoder simulator. CoRR abs/2211.13698 (2022) - 2021
- [j7]Youngsoo Choi, Peter Brown, William J. Arrighi, Robert W. Anderson, Kevin Huynh:
Space-time reduced order model for large-scale linear dynamical systems with application to Boltzmann transport problems. J. Comput. Phys. 424: 109845 (2021) - [j6]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) - [i14]Dylan Matthew Copeland, Siu Wun Cheung, Kevin Huynh, Youngsoo Choi:
Reduced order models for Lagrangian hydrodynamics. CoRR abs/2104.11404 (2021) - [i13]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) - [i12]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) - [i11]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
- [j5]Youngsoo Choi, Gabriele Boncoraglio, Spenser Anderson, David Amsallem, Charbel Farhat:
Gradient-based constrained optimization using a database of linear reduced-order models. J. Comput. Phys. 423: 109787 (2020) - [j4]Youngsoo Choi, Deshawn Coombs, Robert W. Anderson:
SNS: A Solution-Based Nonlinear Subspace Method for Time-Dependent Model Order Reduction. SIAM J. Sci. Comput. 42(2): A1116-A1146 (2020) - [c4]Seikwon Kim, Sunwoo Nam, Youngsoo Choi, Hyowon Kim, Venugopal S. M, Chirag Kataria, Kodam Nagaraju, Surya Kumar, Eun Namgung:
Semantic-based quality of service management for real-time WebRTC streaming service. ISWC (Demos/Industry) 2020: 382-384 - [i10]Chi Hoang, Youngsoo Choi, Kevin Carlberg:
Domain-decomposition least-squares Petrov-Galerkin (DD-LSPG) nonlinear model reduction. CoRR abs/2007.11835 (2020) - [i9]Youngkyu Kim, Youngsoo Choi, David P. Widemann, Tarek I. Zohdi:
A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder. CoRR abs/2009.11990 (2020) - [i8]Sean McBane, Youngsoo Choi:
Component-wise reduced order model lattice-type structure design. CoRR abs/2010.10770 (2020) - [i7]Youngkyu Kim, Youngsoo Choi, David P. Widemann, Tarek I. Zohdi:
Efficient nonlinear manifold reduced order model. CoRR abs/2011.07727 (2020) - [i6]Youngkyu Kim, Karen May Wang, Youngsoo Choi:
Efficient space-time reduced order model for linear dynamical systems in Python using less than 120 lines of code. CoRR abs/2011.10648 (2020)
2010 – 2019
- 2019
- [j3]Youngsoo Choi, Kevin Carlberg:
Space-Time Least-Squares Petrov-Galerkin Projection for Nonlinear Model Reduction. SIAM J. Sci. Comput. 41(1): A26-A58 (2019) - [i5]Youngsoo Choi, Geoffrey Oxberry, Daniel A. White, Trenton Kirchdoerfer:
Accelerating design optimization using reduced order models. CoRR abs/1909.11320 (2019) - [i4]Youngsoo Choi, Peter Brown, Bill Arrighi, Robert W. Anderson:
Space-time reduced order model for large-scale linear dynamical systems with application to Boltzmann transport problems. CoRR abs/1910.01260 (2019) - 2018
- [j2]Kevin Carlberg, Youngsoo Choi, Syuzanna Sargsyan:
Conservative model reduction for finite-volume models. J. Comput. Phys. 371: 280-314 (2018) - [i3]Youngsoo Choi, Deshawn Coombs, Robert W. Anderson:
SNS: A Solution-based Nonlinear Subspace method for time-dependent nonlinear model order reduction. CoRR abs/1809.04064 (2018) - 2017
- [i2]Youngsoo Choi, Kevin Carlberg:
Space-time least-squares Petrov-Galerkin projection for nonlinear model reduction. CoRR abs/1703.04560 (2017) - [i1]Kevin Carlberg, Youngsoo Choi, Syuzanna Sargsyan:
Conservative model reduction for finite-volume models. CoRR abs/1711.11550 (2017) - 2015
- [j1]Youngsoo Choi, Charbel Farhat, Walter Murray, Michael A. Saunders:
A Practical Factorization of a Schur Complement for PDE-Constrained Distributed Optimal Control. J. Sci. Comput. 65(2): 576-597 (2015)
2000 – 2009
- 2005
- [c3]Youngsoo Choi, Sanguk Noh, Kyunghee Choi, Gihyun Jung:
Autonomous and Dependable Recovery Scheme in UPnP Network Settings. IDEAL 2005: 501-506 - 2004
- [c2]Sanguk Noh, Youngsoo Choi, Haesung Seo, Kyunghee Choi, Gihyun Jung:
An Intelligent Topic-Specific Crawler Using Degree of Relevance. IDEAL 2004: 491-498 - 2001
- [c1]Youngsoo Choi, Allan D. Knies, Luke Gerke, Tin-Fook Ngai:
The impact of if-conversion and branch prediction on program execution on the Intel Itanium processor. MICRO 2001: 182-191
Coauthor Index
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