Low-Order Modeling and Machine Learning in Fluid Dynamics: General III
ORAL · R14 · ID: 2665215
Presentations
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Abstract Withdrawn
ORAL Withdrawn
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How much can prompt engineering discover Differential Equation with Large Language Models?
ORAL
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Presenters
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Alejandro Pinto
Rutgers University-New Brunswick
Authors
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Alejandro Pinto
Rutgers University-New Brunswick
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Ruo-Qian Wang
Rutgers University - New Brunswick, Rutgers, the State University of New Jersey
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Tuning synchronization and memory characteristics of unsteady wake flows for physical reservoir computing
ORAL
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Presenters
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Shang-Ru Li
North Carolina State University
Authors
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Shang-Ru Li
North Carolina State University
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Chi-An Yeh
North Carolina State University
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Flow reconstruction from noisy sparse measurements with strictly-enforced convolutional neural networks
ORAL
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Presenters
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Yaxin Mo
Imperial College London
Authors
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Yaxin Mo
Imperial College London
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Luca Magri
Imperial College London, The Alan Turing Institute, PoliTo, Imperial College London, Alan Turing Institute, Politecnico di Torino, Imperial College London, Alan Turing Institute
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Meta-Learning Sampling Method for Quantifying Extreme-Event Statistics
ORAL
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Presenters
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Xianliang Gong
University of Michigan
Authors
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Xianliang Gong
University of Michigan
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Yulin Pan
University of Michigan
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Characteristics of Particle Depositions in Imaging-based Asthmatic Clusters
ORAL
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Presenters
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Xuan Zhang
University of Iowa
Authors
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Xuan Zhang
University of Iowa
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Prathish Kumar Rajaraman
University of Iowa
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Alejandro P Comellas
University of Iowa
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Eric A Hoffman
University of Iowa
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Ching-Long Lin
University of Iowa
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Prediction of isotropic turbulence using conditional diffusion probabilistic models
ORAL
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Presenters
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Jiyeon Kim
Yonsei University
Authors
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Jiyeon Kim
Yonsei University
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Changhoon Lee
Yonsei University
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