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Sungyoon Kim

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Articles

Computer Science > Information Theory

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By Sungyoon Kim, Mert Pilanci
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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Explainable Artificial Intelligence (Xai) for Flood Susceptibility Assessment in Seoul: Leveraging Evolutionary and Bayesian AutoML Optimization

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By Kounghoon Nam, Youngkyu Lee, Sungsu Lee, Sungyoon Kim
| preprints.org
You are already at the latest version This study aims to improve the accuracy and interpretability of flood susceptibility mapping (FSM) by integrating automated machine learning (AutoML) with explainable artificial intelligence (XAI) frameworks. Using spatial data from Seoul, South Korea, ten topographic and environmental factors were selected as model inputs.
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Sustainable synthesis of superhydrophobic perfluorinated nanoporous networks for small molecule separation

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By Sungyoon Kim, Thien Nguyen, Byoungkook Kim, Damien Thirion
| American Chemical Society
RETURN TO JUST ACCEPTED MANUSCRIPTSPREVArticleNEXT Sungyoon Kim Damien Thirion Thien S. Nguyen Byoungkook Kim Nesibe A. Dogan Cafer T. Yavuz LEARN ABOUT THESE METRICS Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.
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