Federated Learning (FL) has gained significant attention as a novel distributed machine learning paradigm that enables collaborative model training while preserving data privacy. However, traditional ...

Transfer learning is a machine learning technique that allows a model trained on one task to be repurposed or fine-tuned for a related task, drastically reducing the amount of data and computational ...

The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...

Transfer learning speeds up model training by reusing pre-trained models for new tasks. It reduces data needs, enhancing performance and progress in new ML applications. Transfer learning is limited ...