李对称性赋能科学计算，新型求解器提升PDE学习精度与效率。
arXiv:2510.25731v2 Announce Type: replace-cross Abstract: Initial-boundary value problems (IBVPs) provide the essential framework for modelling a wide…
双阶段物理信息神经网络破解系数跳变反问题，统计混合模型加持，科学计算新突破。
arXiv:2510.14656v2 Announce Type: replace-cross Abstract: This work proposes a two-stage physics-informed deep learning framework that combines neural…
揭示物理信息神经网络（PINNs）失败的根本原因——过拟合，为改进PINN训练提供新视角
arXiv:2605.30910v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) are a common class of machine learning-based partial differen…
从理论到数值验证，深度解析神经actor-critic求解高维HJB方程的收敛性与性能。
arXiv:2507.06428v2 Announce Type: replace-cross Abstract: We mathematically analyze and numerically study an actor-critic machine learning algorithm f…