4 papers · 1 filter
A Physics-Regulated Neural Framework for Learning 3D Grain Growth Dynamics
Zhihui Tian, Kang Yang, Michael Tonks +2
Grain growth is governed by the reduction in grain boundary energy and exhibits well-established statistical scaling laws. Developing data-driven surrogates that preserve these phy…
Scaling Kinetic Monte-Carlo Simulations of Grain Growth with Combined Convolutional and Graph Neural Networks
Zhihui Tian, Ethan Suwandi, Tomas Oppelstrup +3
Graph neural networks (GNN) have emerged as a promising machine learning method for microstructure simulations such as grain growth. However, accurate modeling of realistic grain b…
Quantifying Heterogeneous Ecosystem Services With Multi-Label Soft Classification
Zhihui Tian, John Upchurch, G. Austin Simon +4
Understanding and quantifying ecosystem services are crucial for sustainable environmental management, conservation efforts, and policy-making. The advancement of remote sensing te…
Wave Physics-informed Matrix Factorizations
Harsha Vardhan Tetali, Joel B. Harley, Benjamin D. Haeffele
With the recent success of representation learning methods, which includes deep learning as a special case, there has been considerable interest in developing techniques that incor…