Search Results for author:
Found 2 papers, 0 papers with code
One-Shot Transfer Learning for Nonlinear ODEs
We introduce a generalizable approach that combines perturbation method and one-shot transfer learning to solve nonlinear ODEs with a single polynomial term, using Physics-Informed Neural Networks (PINNs).
Efficient Natural Gradient Descent Methods for Large-Scale PDE-Based Optimization Problems
We propose efficient numerical schemes for implementing the natural gradient descent (NGD) for a broad range of metric spaces with applications to PDE-based optimization problems.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
