SVD-PINNs: Transfer Learning of Physics-Informed Neural Networks via Singular Value Decomposition. (arXiv:2211.08760v1 [cs.LG])

Physics-informed neural networks (PINNs) have attracted significant attention
for solving partial differential equations (PDEs) in recent years because they
alleviate the curse of dimensionality that appears in traditional methods.
However, the most disadvantage of PINNs is that one neural network corresponds
to one PDE. In practice, we usually need to solve a class of PDEs, not just
one. With the explosive growth of deep learning, many useful techniques in
general deep learning tasks are also suitable for PINNs. Transfer learning …

arxiv networks neural networks physics svd transfer transfer learning value