AIBullisharXiv – CS AI · Mar 34/103
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Astral: training physics-informed neural networks with error majorants
Researchers propose Astral, a new neural network training method for physics-informed neural networks (PiNNs) that uses error majorants instead of residual minimization. The method provides direct upper bounds on errors and demonstrates faster convergence with more reliable error estimation across various partial differential equations.