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Multi-Resolution Active Learning of Fourier Neural Operators
April 1, 2024, 4:42 a.m. | Shibo Li, Xin Yu, Wei Xing, Mike Kirby, Akil Narayan, Shandian Zhe
cs.LG updates on arXiv.org arxiv.org
Abstract: Fourier Neural Operator (FNO) is a popular operator learning framework. It not only achieves the state-of-the-art performance in many tasks, but also is efficient in training and prediction. However, collecting training data for the FNO can be a costly bottleneck in practice, because it often demands expensive physical simulations. To overcome this problem, we propose Multi-Resolution Active learning of FNO (MRA-FNO), which can dynamically select the input functions and resolutions to lower the data cost …
active learning arxiv cs.lg fourier operators resolution type
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