State-of-the-Art Review of Design of Experiments for Physics-Informed Deep Learning

13 February 2022

Papers citing "State-of-the-Art Review of Design of Experiments for Physics-Informed Deep Learning"

5 / 5 papers shown

Title
Scientific Machine Learning Seismology Tomohisa Okazaki PINN AI4CE 50 0 0 27 Sep 2024
A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks Chen-Chun Wu Min Zhu Qinyan Tan Yadhu Kartha Lu Lu 32 352 0 21 Jul 2022
Parallel Physics-Informed Neural Networks via Domain Decomposition K. Shukla Ameya Dilip Jagtap George Karniadakis PINN 101 274 0 20 Apr 2021
Physics-informed neural networks with hard constraints for inverse design Lu Lu R. Pestourie Wenjie Yao Zhicheng Wang F. Verdugo Steven G. Johnson PINN 41 494 0 09 Feb 2021
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 128 508 0 11 Mar 2020