4 papers
An Element-wise RSAV Algorithm for Unconstrained Optimization Problems
Shiheng Zhang, Jiahao Zhang, Jie Shen +1
We present a novel optimization algorithm, element-wise relaxed scalar auxiliary variable (E-RSAV), that satisfies an unconditional energy dissipation law and exhibits improved ali…
NSGA-PINN: A Multi-Objective Optimization Method for Physics-Informed Neural Network Training
Binghang Lu, Christian B. Moya, Guang Lin
This paper presents NSGA-PINN, a multi-objective optimization framework for effective training of Physics-Informed Neural Networks (PINNs). The proposed framework uses the Non-domi…
Efficient Chemical Space Exploration Using Active Learning Based on Marginalized Graph Kernel: an Application for Predicting the Thermodynamic Properties of Alkanes with Molecular Simulation
Yan Xiang, Yu-Hang Tang, Zheng Gong +4
We introduce an explorative active learning (AL) algorithm based on Gaussian process regression and marginalized graph kernel (GPR-MGK) to explore chemical space with minimum cost.…
AMS-Net: Adaptive Multiscale Sparse Neural Network with Interpretable Basis Expansion for Multiphase Flow Problems
Yating Wang, Wing Tat Leung, Guang Lin
In this work, we propose an adaptive sparse learning algorithm that can be applied to learn the physical processes and obtain a sparse representation of the solution given a large…