This repository presents a JAX implementation of the paper entitled "MA Sequential Meta-Transfer (SMT) Learning to Combat Complexities of Physics-Informed Neural Networks: Application to Composites Autoclave Processing". The proposed framework integrates a sequential learning strategy with the meta-transfer learning approach to make the training of PINNs in complex and highly nonlinear system more efficient and adaptable.

Paper: https://arxiv.org/abs/2308.06447

Proposed sequential meta-transfer learning framework

Two sequential learning methods: a) time marching and b) backward-compatibility