We stand with Ukraine

We stand with Ukraine

Kookjin Lee

Orcid: 0000-0003-1557-5862

According to our database¹, Kookjin Lee authored at least 48 papers between 2012 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

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In proceedings

Article

PhD thesis

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Links

On csauthors.net:

Bibliography

2024

The Reconstruction of the Space-Dependent Thermal Conductivity from Sparse Temperature Measurements.

[BibT_eX]

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CoRR, 2024

MaD-Scientist: AI-based Scientist solving Convection-Diffusion-Reaction Equations Using Massive PINN-Based Prior Data.

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CoRR, 2024

FastLRNR and Sparse Physics Informed Backpropagation.

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CoRR, 2024

Latent Space Energy-based Neural ODEs.

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CoRR, 2024

Efficiently Parameterized Neural Metriplectic Systems.

[BibT_eX]

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Nathaniel Trask

CoRR, 2024

Not All Asians are the Same: A Disaggregated Approach to Identifying Anti-Asian Racism in Social Media.

[BibT_eX]

[DOI]

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Sanyam Lakhanpal

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Kyounghee Hazel Kwon

Proceedings of the ACM on Web Conference 2024, 2024

Parameterized Physics-informed Neural Networks for Parameterized PDEs.

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Proceedings of the Forty-first International Conference on Machine Learning, 2024

Learning Flexible Body Collision Dynamics with Hierarchical Contact Mesh Transformer.

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Joon-Young Yang

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Proceedings of the Twelfth International Conference on Learning Representations, 2024

PAC-FNO: Parallel-Structured All-Component Fourier Neural Operators for Recognizing Low-Quality Images.

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Proceedings of the Twelfth International Conference on Learning Representations, 2024

Identifying Contemporaneous and Lagged Dependence Structures by Promoting Sparsity in Continuous-time Neural Networks.

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Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Operator-Learning-Inspired Modeling of Neural Ordinary Differential Equations.

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Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Climate modeling with neural advection-diffusion equation.

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Knowl. Inf. Syst., June, 2023

Graph Convolutions Enrich the Self-Attention in Transformers!

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Nathaniel Trask

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CoRR, 2023

Reduced-order modeling for parameterized PDEs via implicit neural representations.

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CoRR, 2023

Reversible and irreversible bracket-based dynamics for deep graph neural networks.

[BibT_eX]

[DOI]

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Nathaniel Trask

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Hypernetwork-based Meta-Learning for Low-Rank Physics-Informed Neural Networks.

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Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Stochastic Galerkin Methods for Linear Stability Analysis of Systems with Parametric Uncertainty.

[BibT_eX]

[DOI]

Bedrich Sousedík

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SIAM/ASA J. Uncertain. Quantification, March, 2022

Time Series Forecasting with Hypernetworks Generating Parameters in Advance.

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CoRR, 2022

Sinophobia, misogyny, facism, and many more: A multi-ethnic approach to identifying anti-Asian racism in social media.

[BibT_eX]

[DOI]

Sanyam Lakhanpal

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Kyounghee Hazel Kwon

CoRR, 2022

Mining Causality from Continuous-time Dynamics Models: An Application to Tsunami Forecasting.

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CoRR, 2022

Parameter-varying neural ordinary differential equations with partition-of-unity networks.

[BibT_eX]

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Nathaniel Trask

CoRR, 2022

AdamNODEs: When Neural ODE Meets Adaptive Moment Estimation.

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CoRR, 2022

Unsupervised physics-informed disentanglement of multimodal data for high-throughput scientific discovery.

[BibT_eX]

[DOI]

Nathaniel Trask

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Carianne Martinez

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CoRR, 2022

Structure-preserving Sparse Identification of Nonlinear Dynamics for Data-driven Modeling.

[BibT_eX]

[DOI]

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Nathaniel Trask

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Proceedings of the Mathematical and Scientific Machine Learning, 2022

Deep Sequence Models for Packet Stream Analysis and Early Decisions.

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Proceedings of the 47th IEEE Conference on Local Computer Networks, 2022

Significant Enhancement of HCD and TDDB in CMOS FETs by Mechanical Stress.

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Anastasiia Kruv

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Oguzhan O. Okudur

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Alexander Grill

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Proceedings of the IEEE International Reliability Physics Symposium, 2022

2021

Probabilistic partition of unity networks: clustering based deep approximation.

[BibT_eX]

[DOI]

Nathaniel Trask

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Mamikon A. Gulian

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CoRR, 2021

On Surrogate Learning for Linear Stability Assessment of Navier-Stokes Equations with Stochastic Viscosity.

[BibT_eX]

[DOI]

Bedrich Sousedík

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Howard C. Elman

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CoRR, 2021

Large-Scale Flight Frequency Optimization with Global Convergence in the US Domestic Air Passenger Markets.

[BibT_eX]

[DOI]

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Seunghyun Hwang

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Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Machine learning structure preserving brackets for forecasting irreversible processes.

[BibT_eX]

[DOI]

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Nathaniel Trask

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Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Novel Method to Solve Neural Knapsack Problems.

[BibT_eX]

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Ali Seyedmazloom

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Giridhar Kaushik

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Proceedings of the 38th International Conference on Machine Learning, 2021

Climate Modeling with Neural Diffusion Equations.

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Proceedings of the IEEE International Conference on Data Mining, 2021

Partition of Unity Networks: Deep HP-Approximation.

[BibT_eX]

[DOI]

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Nathaniel Trask

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Mamikon A. Gulian

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Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021

Deep Conservation: A Latent-Dynamics Model for Exact Satisfaction of Physical Conservation Laws.

[BibT_eX]

[DOI]

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Kevin T. Carlberg

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation.

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Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders.

[BibT_eX]

[DOI]

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Kevin T. Carlberg

J. Comput. Phys., 2020

Parameterized Neural Ordinary Differential Equations: Applications to Computational Physics Problems.

[BibT_eX]

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CoRR, 2020

Alternating Energy Minimization Methods for Multi-term Matrix Equations.

[BibT_eX]

[DOI]

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Howard C. Elman

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Catherine E. Powell

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CoRR, 2020

2019

A Low-Rank Solver for the Navier-Stokes Equations with Uncertain Viscosity.

[BibT_eX]

[DOI]

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Howard C. Elman

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Bedrich Sousedík

SIAM/ASA J. Uncertain. Quantification, 2019

Solving Large-Scale 0-1 Knapsack Problems and its Application to Point Cloud Resampling.

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Giridhar Ramachandran

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Ali Seyedmazloom

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CoRR, 2019

Two Problems in Knowledge Graph Embedding: Non-Exclusive Relation Categories and Zero Gradients.

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Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

Inexact Methods for Symmetric Stochastic Eigenvalue Problems.

[BibT_eX]

[DOI]

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Bedrich Sousedík

SIAM/ASA J. Uncertain. Quantification, 2018

Stochastic Least-Squares Petrov-Galerkin Method for Parameterized Linear Systems.

[BibT_eX]

[DOI]

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Howard C. Elman

SIAM/ASA J. Uncertain. Quantification, 2018

On Integrating Knowledge Graph Embedding into SPARQL Query Processing.

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Proceedings of the 2018 IEEE International Conference on Web Services, 2018

MMGAN: Manifold-Matching Generative Adversarial Networks.

[BibT_eX]

[DOI]

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Joel Ruben Antony Moniz

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David Keetae Park

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Tanmoy Chakraborty

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Proceedings of the 24th International Conference on Pattern Recognition, 2018

2017

A Preconditioned Low-Rank Projection Method with a Rank-Reduction Scheme for Stochastic Partial Differential Equations.

[BibT_eX]

[DOI]

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Howard C. Elman

SIAM J. Sci. Comput., 2017

MMGAN: Manifold Matching Generative Adversarial Network for Generating Images.

[BibT_eX]

[DOI]

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Joel Ruben Antony Moniz

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Tanmoy Chakraborty

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CoRR, 2017

2012

A group-based communication scheme based on the location information of MTC devices in cellular networks.

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Proceedings of IEEE International Conference on Communications, 2012

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