Peng Yin

EvoPINN: Agentic Discovery of Executable Algorithms for Physics-Informed Neural Networks

EvoPINN is proposed, an agentic framework that reformulates PINN development from labor-intensive manual design into a rigorous, execution-grounded algorithm discovery problem, and autonomously invented SLRC-PINN, a novel architecture whose performance gains persist under rigorous parameter-matched comparisons.