no code implementations • 8 Apr 2024 • Ming Zhong, Dehao Liu, Raymundo Arroyave, Ulisses Braga-Neto
This paper proposes a semi-supervised methodology for training physics-informed machine learning methods.
no code implementations • 1 May 2020 • Dehao Liu, Yan Wang
Data sparsity is a common issue to train machine learning tools such as neural networks for engineering and scientific applications, where experiments and simulations are expensive.