AINeutralarXiv – CS AI · 8h ago6/10
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naPINN: Noise-Adaptive Physics-Informed Neural Networks for Recovering Physics from Corrupted Measurement
Researchers introduce naPINN (Noise-Adaptive Physics-Informed Neural Networks), a novel machine learning approach that recovers accurate physical equations from corrupted or noisy measurement data without requiring prior knowledge of noise characteristics. The method uses energy-based models to identify and filter outliers while maintaining data integrity, substantially outperforming existing robust PINN methods across benchmark tests with non-Gaussian noise and varying outlier rates.