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Yongseok Jo

Seoul National University

13

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34

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The CAMELS Multifield Dataset: Learning the Universe's Fundamental Parameters with Artificial Intelligence

2021 arXiv: Learning
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Dark Matter Deficient Galaxies Produced Via High-velocity Galaxy Collisions In High-resolution Numerical Simulations

2020 arXiv: Astrophysics of Galaxies
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Keystone 영역에 국한된 비중격 농양 1예: 비출혈로 시행한 전기 소작이 원인으로 추정되는 사례

2020
- Yongseok Jo
- Ick Soo Choi
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From dark matter to baryons in a simulated universe via machine learning

2020
- Yongseok Jo
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Dark Matter Deficient Galaxies Produced via High-velocity Galaxy Collisions in High-resolution Numerical Simulations

2020 The Astrophysical Journal
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The fate of an infalling circumgalactic gas clump and the growth of the central massive black hole in a high-redshift quasar

2020
- Yongseok Jo
- Ji Hoon Kim
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Machine-assisted Semi-Simulation Model (MSSM): Estimating Galactic Baryonic Properties from Their Dark Matter Using A Machine Trained on Hydrodynamic Simulations

2019 Monthly Notices of the Royal Astronomical Society
- Yongseok Jo
- Jihoon Kim
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High-redshift Galaxy Formation with Self-consistently Modeled Stars and Massive Black Holes: Stellar Feedback and Quasar Growth.

2019 arXiv: Astrophysics of Galaxies
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