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Seminars
- FIELD
- AI and Natural Sciences
- DATE
-
Jan 04 (Thu), 2024
- TIME
- 14:00 ~ 15:30
- PLACE
- 7323
- SPEAKER
- 조우진
- HOST
- Lee, Jaeyong
- INSTITUTE
- M.S. student in the Department of AI at Yonsei University (Advised by Prof.Noseong Park)
- TITLE
- Scientific Machine Learning: Solving Physical Problems with PINN and Neural Operators
- ABSTRACT
- In various engineering and applied science applications, repetitive numerical simulations of partial differential equations (PDEs) for varying input parameters are often required (e.g., aircraft shape optimization over many design parameters) and solvers are required to perform rapid execution. In the field of Scientific Machine Learning, various methodologies have evolved to address the shortcomings of traditional numerical analysis methods and expedite problem-solving. Among these, PINN (Physics-informed Neural Networks) and Neural Operators stand out as highly effective models for resolving physical problems. In this seminar, I'll introduce PINN, Neural Operators, and present my research associated with these techniques.
- FILE
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