MODAL@UNINA

Archivio mensile 26 Luglio 2022

Scientific Machine Learning Through Physics–Informed Neural Networks: Where we are and What’s Next

We are excited to share that the Journal of Scientific Computing has published our comprehensive review paper on “Scientific Machine Learning Through Physics–Informed Neural Networks: Where we are and What’s Next”. 

The paper focuses on Physics-Informed Neural Networks (PINN), a novel approach where neural networks are used to solve complex mathematical equations, including Partial Differential Equations (PDEs). The review summarizes the literature on PINNs and their advantages and disadvantages.

We hope this review paper will be beneficial to researchers in the field of scientific machine learning and inspire future work on this promising approach.

Find out more at: https://link.springer.com/article/10.1007/s10915-022-01939-z