most citedHammering at the entropy: A GENERIC-guided approach to learning polymeric rheological constitutive equations using PINNs

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cs.LG2025

PINN Balls: Scaling Second-Order Methods for PINNs with Domain Decomposition and Adaptive Sampling

Andrea Bonfanti, Ismael Medina, Roman List +3

Recent advances in Scientific Machine Learning have shown that second-order methods can enhance the training of Physics-Informed Neural Networks (PINNs), making them a suitable alt…