Transfer learning, which transfers patterns learned on a source dataset to a related target dataset for constructing prediction models, has been shown effective in many applications. In this paper, we ...

Transfer learning refers to the process of adapting a model trained on a source task to a target task. While kernel methods are conceptually and computationally simple models that are competitive on a ...

Mingai Li, received her B.Sc. degree and M.Sc. degree from Daqing Petroleum Institute, Heilongjiang, China, in 1987 and 1990 respectively, and Ph.D. degree from Beijing University of Technology, ...

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 ...