The impact of if-conversion and branch prediction on program execution on the Intel Itanium processor. - Youngsoo Choi; Allan D. Knies; Luke Gerke; Tin-Fook Ngai (MICRO, 2001)

An Intelligent Topic-Specific Crawler Using Degree of Relevance. - Sanguk Noh; Youngsoo Choi; Haesung Seo; Kyunghee Choi; Gihyun Jung (IDEAL, 2004)

Autonomous and Dependable Recovery Scheme in UPnP Network Settings. - Youngsoo Choi; Sanguk Noh; Kyunghee Choi; Gihyun Jung (IDEAL, 2005)

A Practical Factorization of a Schur Complement for PDE-Constrained Distributed Optimal Control. - Youngsoo Choi; Charbel Farhat; Walter Murray; Michael A. Saunders (J. Sci. Comput., 2015)

SNS: A Solution-based Nonlinear Subspace method for time-dependent nonlinear model order reduction. - Youngsoo Choi; Deshawn Coombs; Robert W. Anderson (CoRR, 2018)

Conservative model reduction for finite-volume models. - Kevin Carlberg; Youngsoo Choi; Syuzanna Sargsyan (J. Comput. Phys., 2018)

Accelerating design optimization using reduced order models. - Youngsoo Choi; Geoffrey Oxberry; Daniel A. White; Trenton Kirchdoerfer (CoRR, 2019)

Space-time reduced order model for large-scale linear dynamical systems with application to Boltzmann transport problems. - Youngsoo Choi; Peter Brown; Bill Arrighi; Robert W. Anderson (CoRR, 2019)

Space-Time Least-Squares Petrov-Galerkin Projection for Nonlinear Model Reduction. - Youngsoo Choi; Kevin Carlberg (SIAM J. Sci. Comput., 2019)

Semantic-based quality of service management for real-time WebRTC streaming service. - Seikwon Kim; Sunwoo Nam; Youngsoo Choi; Hyowon Kim; Venugopal S. M; Chirag Kataria; Kodam Nagaraju; Surya Kumar; Eun Namgung (ISWC (Demos/Industry), 2020)

Domain-decomposition least-squares Petrov-Galerkin (DD-LSPG) nonlinear model reduction. - Chi Hoang; Youngsoo Choi; Kevin Carlberg (CoRR, 2020)

Component-wise reduced order model lattice-type structure design. - Sean McBane; Youngsoo Choi (CoRR, 2020)

Efficient nonlinear manifold reduced order model. - Youngkyu Kim; Youngsoo Choi; David P. Widemann; Tarek I. Zohdi (CoRR, 2020)

Efficient space-time reduced order model for linear dynamical systems in Python using less than 120 lines of code. - Youngkyu Kim; Karen May Wang; Youngsoo Choi (CoRR, 2020)

Gradient-based constrained optimization using a database of linear reduced-order models. - Youngsoo Choi; Gabriele Boncoraglio; Spenser Anderson; David Amsallem; Charbel Farhat (J. Comput. Phys., 2020)

SNS: A Solution-Based Nonlinear Subspace Method for Time-Dependent Model Order Reduction. - Youngsoo Choi; Deshawn Coombs; Robert W. Anderson (SIAM J. Sci. Comput., 2020)

Reduced order models for Lagrangian hydrodynamics. - Dylan Matthew Copeland; Siu Wun Cheung; Kevin Huynh; Youngsoo Choi (CoRR, 2021)

Non-intrusive reduced order modeling of natural convection in porous media using convolutional autoencoders: comparison with linear subspace techniques. - Teeratorn Kadeethum; Francesco Ballarin; Youngsoo Choi; Daniel O'Malley; Hongkyu Yoon; Nikolaos Bouklas (CoRR, 2021)

Space-time reduced order model for large-scale linear dynamical systems with application to Boltzmann transport problems. - Youngsoo Choi; Peter Brown; William J. Arrighi; Robert W. Anderson; Kevin Huynh (J. Comput. Phys., 2021)

A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks. - Teeratorn Kadeethum; Daniel O'Malley; Jan Niklas Fuhg; Youngsoo Choi; Jonghyun Lee 005; Hari S. Viswanathan; Nikolaos Bouklas (Nat. Comput. Sci., 2021)

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 (CoRR, 2022)

LaSDI: Parametric Latent Space Dynamics Identification. - William Fries; Xiaolong He 001; Youngsoo Choi (CoRR, 2022)

Stress-constrained topology optimization of lattice-like structures using component-wise reduced order models. - Sean McBane; Youngsoo Choi; Karen Willcox (CoRR, 2022)

Using Conservation Laws to Infer Deep Learning Model Accuracy of Richtmyer-Meshkov Instabilities. - Charles F. Jekel; Dane M. Sterbentz; Sylvie Aubry; Youngsoo Choi; Daniel A. White; Jonathan L. Belof (CoRR, 2022)

Certified data-driven physics-informed greedy auto-encoder simulator. - Xiaolong He 001; Youngsoo Choi; William D. Fries; Jonathan L. Belof; Jiun-Shyan Chen (CoRR, 2022)

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 (Comput. Geosci., 2022)

A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder. - Youngkyu Kim; Youngsoo Choi; David P. Widemann; Tarek I. Zohdi (J. Comput. Phys., 2022)

A Novel Approach for Estimating Vehicle Speed in Nighttime Traffic Accidents from Daytime Video Information. - Youngsoo Choi; Yongmun Yun; Woo-Jeong Jeon; Seung-Hyun Kong (ITSC, 2023)

Epistemic Uncertainty-Aware Barlow Twins Reduced Order Modeling for Nonlinear Contact Problems. - Teeratorn Kadeethum; John D. Jakeman; Youngsoo Choi; Nikolaos Bouklas; Hongkyu Yoon (IEEE Access, 2023)

A fast and accurate domain-decomposition nonlinear manifold reduced order model. - Alejandro N. Diaz; Youngsoo Choi; Matthias Heinkenschloss (CoRR, 2023)

Data-scarce surrogate modeling of shock-induced pore collapse process. - Siu Wun Cheung; Youngsoo Choi; H. Keo Springer; Teeratorn Kadeethum (CoRR, 2023)

GPLaSDI: Gaussian Process-based Interpretable Latent Space Dynamics Identification through Deep Autoencoder. - Christophe Bonneville; Youngsoo Choi; Debojyoti Ghosh; Jonathan L. Belof (CoRR, 2023)

Progressive reduced order modeling: empowering data-driven modeling with selective knowledge transfer. - Teeratorn Kadeethum; Daniel O'Malley; Youngsoo Choi; Hari S. Viswanathan; Hongkyu Yoon (CoRR, 2023)

Accelerating Kinetic Simulations of Electrostatic Plasmas with Reduced-Order Modeling. - Ping-Hsuan Tsai; Seung Whan Chung; Debojyoti Ghosh; John Loffeld; Youngsoo Choi; Jonathan L. Belof (CoRR, 2023)

Weak-Form Latent Space Dynamics Identification. - April Tran; Xiaolong He 001; Daniel A. Messenger; Youngsoo Choi; David M. Bortz (CoRR, 2023)

Reduced-order modeling for parameterized PDEs via implicit neural representations. - Tianshu Wen; Kookjin Lee; Youngsoo Choi (CoRR, 2023)

A Data-Driven, Non-Linear, Parameterized Reduced Order Model of Metal 3D Printing. - Aaron L. Brown; Eric B. Chin; Youngsoo Choi; Saad A. Khairallah; Joseph T. McKeown (CoRR, 2023)

Accelerating Flow Simulations using Online Dynamic Mode Decomposition. - Seung-Won Suh; Seung Whan Chung; Peer-Timo Bremer; Youngsoo Choi (CoRR, 2023)

Nonlinear-manifold reduced order models with domain decomposition. - Alejandro N. Diaz; Youngsoo Choi; Matthias Heinkenschloss (CoRR, 2023)

Data-Driven Autoencoder Numerical Solver with Uncertainty Quantification for Fast Physical Simulations. - Christophe Bonneville; Youngsoo Choi; Debojyoti Ghosh; Jonathan L. Belof (CoRR, 2023)

Local Lagrangian reduced-order modeling for the Rayleigh-Taylor instability by solution manifold decomposition. - Siu Wun Cheung; Youngsoo Choi; Dylan Matthew Copeland; Kevin Huynh (J. Comput. Phys., 2023)

gLaSDI: Parametric physics-informed greedy latent space dynamics identification. - Xiaolong He 001; Youngsoo Choi; William D. Fries; Jonathan L. Belof; Jiun-Shyan Chen (J. Comput. Phys., 2023)

On the implementation of a quasi-Newton interior-point method for PDE-constrained optimization using finite element discretizations. - Cosmin G. Petra; Miguel A. Salazar de Troya; Noemi Petra; Youngsoo Choi; Geoffrey M. Oxberry; Daniel A. Tortorelli (Optim. Methods Softw., 2023)

Parametric dynamic mode decomposition for reduced order modeling. - Quincy A. Huhn; Mauricio E. Tano; Jean C. Ragusa; Youngsoo Choi (J. Comput. Phys., 2023)

Train Small, Model Big: Scalable Physics Simulators via Reduced Order Modeling and Domain Decomposition. - 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 (CoRR, 2024)

tLaSDI: Thermodynamics-informed latent space dynamics identification. - Jun Sur Richard Park; Siu Wun Cheung; Youngsoo Choi; Yeonjong Shin (CoRR, 2024)

A Comprehensive Review of Latent Space Dynamics Identification Algorithms for Intrusive and Non-Intrusive Reduced-Order-Modeling. - Christophe Bonneville; Xiaolong He 001; 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; et al. (CoRR, 2024)

Physics-informed active learning with simultaneous weak-form latent space dynamics identification. - Xiaolong He 001; April Tran; David M. Bortz; Youngsoo Choi (CoRR, 2024)

Data-driven Virtual Test-bed of the Blown Powder Directed Energy Deposition Process. - Michael Juhasz; Eric B. Chin; Youngsoo Choi; Joseph T. McKeown; Saad A. Khairallah (CoRR, 2024)

Scaled-up prediction of steady Navier-Stokes equation with component reduced order modeling. - Seung Whan Chung; Youngsoo Choi; Pratanu Roy; Thomas Roy; Tiras Y. Lin; Du T. Nguyen; Christopher Hahn; Eric B. Duoss; Sarah E. Baker (CoRR, 2024)

Scalable physics-guided data-driven component model reduction for steady Navier-Stokes flow. - Seung Whan Chung; Youngsoo Choi; Pratanu Roy; Thomas Roy; Tiras Y. Lin; Du T. Nguyen; Christopher Hahn; Eric B. Duoss; Sarah E. Baker (CoRR, 2024)

Quantifying Qualitative Insights: Leveraging LLMs to Market Predict. - Hoyoung Lee; Youngsoo Choi; Yuhee Kwon (CoRR, 2024)

Scalable nonlinear manifold reduced order model for dynamical systems. - Ivan Zanardi; Alejandro N. Diaz; Seung Whan Chung; Marco Panesi; Youngsoo Choi (CoRR, 2024)

Data-Driven, Parameterized Reduced-order Models for Predicting Distortion in Metal 3D Printing. - Indu Kant Deo; Youngsoo Choi; Saad A. Khairallah; Alexandre Reikher; Maria Strantza (CoRR, 2024)

Physics-informed reduced order model with conditional neural fields. - Minji Kim; Tianshu Wen; Kookjin Lee; Youngsoo Choi (CoRR, 2024)

Theory and numerics of subspace approximation of eigenvalue problems. - Siu Wun Cheung; Youngsoo Choi; Seung Whan Chung; Jean-Luc Fattebert; Coleman Kendrick; Daniel Osei-Kuffuor (CoRR, 2024)

S-OPT: A Points Selection Algorithm for Hyper-Reduction in Reduced Order Models. - Jessica T. Lauzon; Siu Wun Cheung; Yeonjong Shin; Youngsoo Choi; Dylan Matthew Copeland; Kevin Huynh (SIAM J. Sci. Comput., 2024)

Defining Foundation Models for Computational Science: A Call for Clarity and Rigor. - Youngsoo Choi; Siu Wun Cheung; Youngkyu Kim; Ping-Hsuan Tsai; Alejandro N. Diaz; Ivan Zanardi; Seung Whan Chung; Dylan Matthew Copeland; Coleman Kendrick; William Anderson; Traian Iliescu; Matthias Heinkenschloss (CoRR, 2025)

Thermodynamically Consistent Latent Dynamics Identification for Parametric Systems. - Xiaolong He 001; Yeonjong Shin; Anthony Gruber; Sohyeon Jung; Kookjin Lee; Youngsoo Choi (CoRR, 2025)

mLaSDI: Multi-stage latent space dynamics identification. - William Anderson; Seung Whan Chung; Youngsoo Choi (CoRR, 2025)