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cs.AI2026
PINNMorph: Evolving Online Adaptation Policies for Physics-Informed Neural Networks
Xu Yang, Mingyang Yu, Jun Zhang +2
Physics-informed neural networks (PINNs) provide a learning-based framework for solving partial differential equations (PDEs), yet their training behavior can change substantially…
cs.AI2026
PINNForge: Execution-Grounded Evolutionary Design of Physics-Informed Neural Networks
Mingyang Yu, Xu Yang, Jun Zhang +3
Physics-informed neural networks (PINNs) require coordinated choices across representation, architecture, sampling, constraints, loss construction, and optimization, yet effective…