2 papers
math.NA2025
Spectral-Prior Guided Multistage Physics-Informed Neural Networks for Highly Accurate PDE Solutions
Yuzhen Li, Liang Li, Stéphane Lanteri +1
Physics-Informed Neural Networks (PINNs) are becoming a popular method for solving PDEs, due to their mesh-free nature and their ability to handle high-dimensional problems where t…
cs.CE2025
BO-SA-PINNs: Self-adaptive physics-informed neural networks based on Bayesian optimization for automatically designing PDE solvers
Rui Zhang, Liang Li, Stéphane Lanteri +2
Physics-informed neural networks (PINNs) is becoming a popular alternative method for solving partial differential equations (PDEs). However, they require dedicated manual modifica…