Sobolev training for operator learning

초록

This study explores the impact of Sobolev Training on operator learning frameworks to enhance model performance. Our research shows that integrating derivative information into the loss function significantly improves the training process. We employ an algorithm that approximates derivatives on irregular meshes in conjunction with operator learning. Our results, supported by experimental evidence and theoretical analysis, demonstrate the effectiveness of Sobolev Training in operator learning.

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