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2025 ICML ICML 2025

Neural Interpretable PDEs: Harmonizing Fourier Insights with Attention for Scalable and Interpretable Physics Discovery

Abstract

No abstract available. No abstract was captured for this paper when its proceedings were scraped - most often an older edition published without one online. How the corpus is built.

Authors

Ning Liu, Yue Yu

Topics

Artificial Intelligence > Core AI > Interpretability Machine Learning > Application Areas > Efficient Computing Deep Learning > Architectures > Neural Networks

Keywords

interpretability neural operator kernel network fourier space scalable nonlocal attention operators
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