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Yoonsang Lee

Orcid: 0000-0002-5573-9414

Affiliations:
  • Dartmouth College, Hanover, NH, USA
  • New York University, NY, USA (since 2013)
  • Lawrence Berkeley National Laboratory, CA, USA (2017 - 2018)
  • University of Texas at Austin, USA (PhD 2013)


According to our database1, Yoonsang Lee authored at least 23 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Links

Online presence:

On csauthors.net:

Bibliography

2024
Learning In-Between Imagery Dynamics via Physical Latent Spaces.
[BibTeX]
[DOI]
Jihun Han
,
Yoonsang Lee
,
Anne Gelb
SIAM J. Sci. Comput., 2024

Learning the Dynamics for Unknown Hyperbolic Conservation Laws Using Deep Neural Networks.
[BibTeX]
[DOI]
Zhen Chen
,
Anne Gelb
,
Yoonsang Lee
SIAM J. Sci. Comput., 2024

A structurally informed data assimilation approach for nonlinear partial differential equations.
[BibTeX]
[DOI]
Tongtong Li
,
Anne Gelb
,
Yoonsang Lee
J. Comput. Phys., 2024

A stochastic approach for elliptic problems in perforated domains.
[BibTeX]
[DOI]
Jihun Han
,
Yoonsang Lee
J. Comput. Phys., 2024

Entropy stable conservative flux form neural networks.
[BibTeX]
[DOI]
Lizuo Liu
,
Tongtong Li
,
Anne Gelb
,
Yoonsang Lee
CoRR, 2024

Sampling error mitigation through spectrum smoothing in ensemble data assimilation.
[BibTeX]
[DOI]
Bosu Choi
,
Yoonsang Lee
CoRR, 2024

2023
Inhomogeneous regularization with limited and indirect data.
[BibTeX]
[DOI]
Jihun Han
,
Yoonsang Lee
J. Comput. Appl. Math., August, 2023

A Neural Network Approach for Homogenization of Multiscale Problems.
[BibTeX]
[DOI]
Jihun Han
,
Yoonsang Lee
Multiscale Model. Simul., June, 2023

Improving numerical accuracy for the viscous-plastic formulation of sea ice.
[BibTeX]
[DOI]
Tongtong Li
,
Anne Gelb
,
Yoonsang Lee
J. Comput. Phys., 2023

An analysis of the derivative-free loss method for solving PDEs.
[BibTeX]
[DOI]
Jihun Han
,
Yoonsang Lee
CoRR, 2023

Weighted inhomogeneous regularization for inverse problems with indirect and incomplete measurement data.
[BibTeX]
[DOI]
Bosu Choi
,
Jihun Han
,
Yoonsang Lee
CoRR, 2023

Hierarchical Learning to Solve PDEs Using Physics-Informed Neural Networks.
[BibTeX]
[DOI]
Jihun Han
,
Yoonsang Lee
Proceedings of the Computational Science - ICCS 2023, 2023

2022
Designing Neural Networks for Hyperbolic Conservation Laws.
[BibTeX]
[DOI]
Zhen Chen
,
Anne Gelb
,
Yoonsang Lee
CoRR, 2022

2021
l<sub>p</sub> Regularization for Ensemble Kalman Inversion.
[BibTeX]
[DOI]
Yoonsang Lee
SIAM J. Sci. Comput., 2021

Hierarchical Learning to Solve Partial Differential Equations Using Physics-Informed Neural Networks.
[BibTeX]
[DOI]
Jihun Han
,
Yoonsang Lee
CoRR, 2021

Inhomogenous Regularization with Limited and Indirect Data.
[BibTeX]
[DOI]
Jihun Han
,
Yoonsang Lee
CoRR, 2021

Sampling error correction in ensemble Kalman inversion.
[BibTeX]
[DOI]
Yoonsang Lee
CoRR, 2021

2017
Stochastic Superparameterization and Multiscale Filtering of Turbulent Tracers.
[BibTeX]
[DOI]
Yoonsang Lee
,
Andrew J. Majda
,
Di Qi
Multiscale Model. Simul., 2017

2016
Multiscale numerical methods for passive advection-diffusion in incompressible turbulent flow fields.
[BibTeX]
[DOI]
Yoonsang Lee
,
Björn Engquist
J. Comput. Phys., 2016

2015
Multiscale Methods for Data Assimilation in Turbulent Systems.
[BibTeX]
[DOI]
Yoonsang Lee
,
Andrew J. Majda
Multiscale Model. Simul., 2015

Numerical Schemes for Stochastic Backscatter in the Inverse Cascade of Quasigeostrophic Turbulence.
[BibTeX]
[DOI]
Ian G. Grooms
,
Yoonsang Lee
,
Andrew J. Majda
Multiscale Model. Simul., 2015

2014
Ensemble Kalman filters for dynamical systems with unresolved turbulence.
[BibTeX]
[DOI]
Ian G. Grooms
,
Yoonsang Lee
,
Andrew J. Majda
J. Comput. Phys., 2014

2013
A Multiscale Method for Highly Oscillatory Dynamical Systems Using a Poincaré Map Type Technique.
[BibTeX]
[DOI]
Gil Ariel
,
Björn Engquist
,
S. Kim
,
Yoonsang Lee
,
Richard Tsai
J. Sci. Comput., 2013


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