NSGA-PINN: A Multi-Objective Optimization Method for Physics-Informed Neural Network Training

3 March 2023

Papers citing "NSGA-PINN: A Multi-Objective Optimization Method for Physics-Informed Neural Network Training"

5 / 5 papers shown

Title
Physics-informed neural networks with hard constraints for inverse design Lu Lu R. Pestourie Wenjie Yao Zhicheng Wang F. Verdugo Steven G. Johnson PINN 92 515 0 09 Feb 2021
Non-convergence of stochastic gradient descent in the training of deep neural networks Patrick Cheridito Arnulf Jentzen Florian Rossmannek 48 37 0 12 Jun 2020
Physics-informed learning of governing equations from scarce data Zhao Chen Yang Liu Hao Sun PINN AI4CE 60 393 0 05 May 2020
Non-convex Optimization for Machine Learning Prateek Jain Purushottam Kar 153 486 0 21 Dec 2017
Automatic differentiation in machine learning: a survey A. G. Baydin Barak A. Pearlmutter Alexey Radul J. Siskind PINN AI4CE ODL 156 2,800 0 20 Feb 2015