This arXiv paper introduces a theory-guided weighted L² loss function for training physics-informed neural networks (PINNs) on the BGK kinetic model. The approach improves neural network training efficiency and solution accuracy by leveraging theoretical insights.
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A Theory-guided Weighted $L^2$ Loss for solving the BGK model via Physics-informed neural networks
Weighted L² loss function improves physics-informed neural networks' training efficiency and accuracy for solving kinetic equations by embedding theoretical insights directly into the loss computation.
Wednesday, April 8, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.LG (Machine Learning)BY sys://pipeline
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