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Center for Computing Research

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Publication	Type	Year
Deep Learning for Parameterized Dynamical Systems Weekly seminar at Yonsei University Kookjin Lee	Presentation (non-conference) – 2021 Presentation (non-conference)	2021
Deep Conservation: A Latent-Dynamics Model for Exact Satisfaction of Physical Conservation Laws 35th AAAI conference on Artificial Intelligence Kookjin Lee, Kevin Carlberg https://www.osti.gov/search/identifier:1848048	Conference Poster – 2021 Conference Poster	2021
Deep Conservation: A Latent-Dynamics Model for Exact Satisfaction of Physical Conservation Laws 35th AAAI conference on Artificial Intelligence Kookjin Lee https://www.osti.gov/search/identifier:1840096	Conference Presentation – 2021 Conference Presentation	2021
Deep Conservation: A latent dynamics model for exact satisfaction of physical conservation laws 35th AAAI conference on Artificial Intelligence Kookjin Lee, Kevin Carlberg https://www.osti.gov/search/identifier:1877797	Conference Paper – 2020 Conference Paper	2020
DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation 35th AAAI conference on Artificial Intelligence Jungeun Kim, Kookjin Lee, Dongeun Lee, Sheo Yon Jin, Noseong Park https://www.osti.gov/search/identifier:1836905	Conference Paper – 2020 Conference Paper	2020
Parameterized Neural Ordinary Differential Equations: Applications to Computational Physics Problems Kookjin Lee, Eric Joshua Parish https://www.osti.gov/search/identifier:1706214	Report – 2020 Report	2020
Predictive Skill of Deep Learning Models Trained on Limited Sequence Data Cosmin Safta, Kookjin Lee, Jaideep Ray https://www.osti.gov/search/identifier:1688570	SAND Report – 2020 SAND Report	2020
Alternating Energy Minimization Methods For Multi-term Matrix Equations SIAM Journal on Scientific Computing Kookjin Lee, Howard Elman, Catherine Powell, Dongeun Lee	Journal Article – 2020 Journal Article	2020
Two Problems in Knowledge Graph Embedding: Non-Exclusive Relation Categories and Zero Gradients 2019 IEEE International Conference on Big Data Kookjin Lee, Nasheen Nur, Noseong Park, Hyunjoong Kang, Soonhyeon Kwon https://www.osti.gov/search/identifier:1643290	Conference Paper – 2019 Conference Paper	2019
Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders Elsevier Journal of Computational Physics Kookjin Lee, Kookjin Lee, Kevin Carlberg, Kevin Carlberg https://www.osti.gov/search/identifier:1574441	Journal Article – 2019 Journal Article	2019
Deep Conservation: A latent dynamics model for exact satisfaction of physical conservation laws Kookjin Lee, Kevin Carlberg https://www.osti.gov/search/identifier:1569346	Report – 2019 Report	2019
Breaking Kolmogorov-width barriers using deep learning Physics-Informed Machine Learning Kevin Thomas Carlberg, Kookjin Lee	Conference Paper – 2019 Conference Paper	2019
Nonlinear model reduction: Using machine learning to enable rapid simulation of extreme-scale physics models Stanford ICME Xpo Kevin Thomas Carlberg, Kookjin Lee https://www.osti.gov/search/identifier:1645297	Presentation (non-conference) – 2019 Presentation (non-conference)	2019
Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders Research Challenges and Opportunities at the interface of Machine Learning and Uncertainty Quantification Kevin Thomas Carlberg, Kookjin Lee	Abstract – 2019 Abstract	2019
Inexact Methods For Symmetric Stochastic Eigenvalue Problems SIAM Conference on Computational Science and Engineering Kookjin Lee, Bedrich Sousedik https://www.osti.gov/search/identifier:1602123	Conference Paper – 2019 Conference Paper	2019
Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders Journal of Computational Physics Kevin Thomas Carlberg, Kookjin Lee https://www.osti.gov/search/identifier:1581987	Journal Article – 2019 Journal Article	2019
Model reduction for nonlinear dynamical systems using deep convolutional autoencoders Bay Area Scientific Computing Day 2018 Kookjin Lee, Kevin Thomas Carlberg https://www.osti.gov/search/identifier:1761319	Conference Paper – 2018 Conference Paper	2018
Inexact Methods For Symmetric Stochastic Eigenvalue Problems SIAM/ASC Journal of Uncertainty Quantification Kookjin Lee, Bedrich (UMBC) Sousedik https://www.osti.gov/search/identifier:1498483	Journal Article – 2018 Journal Article	2018
Document Title	Type	Year