Gyutaek Oh

Orcid: 0000-0002-7689-1538

According to our database1, Gyutaek Oh authored at least 15 papers between 2019 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Annealed Score-Based Diffusion Model for MR Motion Artifact Reduction.
IEEE Trans. Computational Imaging, 2024

Unpaired deep learning for pharmacokinetic parameter estimation from dynamic contrast-enhanced MRI without AIF measurements.
NeuroImage, 2024

2023
scHyena: Foundation Model for Full-Length Single-Cell RNA-Seq Analysis in Brain.
CoRR, 2023

Unpaired Deep Learning for Pharmacokinetic Parameter Estimation from Dynamic Contrast-Enhanced MRI.
CoRR, 2023

Annealed Score-Based Diffusion Model for MR Motion Artifact Reduction.
CoRR, 2023

2022
Unsupervised resolution-agnostic quantitative susceptibility mapping using adaptive instance normalization.
Medical Image Anal., 2022

2021
Unpaired MR Motion Artifact Deep Learning Using Outlier-Rejecting Bootstrap Aggregation.
IEEE Trans. Medical Imaging, 2021

2020
Unpaired Deep Learning for Accelerated MRI Using Optimal Transport Driven CycleGAN.
IEEE Trans. Computational Imaging, 2020

Optimal Transport Driven CycleGAN for Unsupervised Learning in Inverse Problems.
SIAM J. Imaging Sci., 2020

Geometric Approaches to Increase the Expressivity of Deep Neural Networks for MR Reconstruction.
IEEE J. Sel. Top. Signal Process., 2020

CycleQSM: Unsupervised QSM Deep Learning using Physics-Informed CycleGAN.
CoRR, 2020

Unsupervised MR Motion Artifact Deep Learning using Outlier-Rejecting Bootstrap Aggregation.
CoRR, 2020

Unsupervised Learning for Compressed Sensing MRI Using Cyclegan.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Optimal Transport Structure of CycleGAN for Unsupervised Learning for Inverse Problems.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Optimal Transport, CycleGAN, and Penalized LS for Unsupervised Learning in Inverse Problems.
CoRR, 2019


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