15 citations · 17 across the 3 of their papers we have counts for
4 papers
Machine Learning-Assisted Exploration of Thermally Conductive Polymers Based on High-Throughput Molecular Dynamics Simulations
Ruimin Ma, Hanfeng Zhang, Jiaxin Xu +4
Finding amorphous polymers with higher thermal conductivity is important, as they are ubiquitous in heat transfer applications. With recent progress in material informatics, machin…
Super-resolution and denoising of fluid flow using physics-informed convolutional neural networks without high-resolution labels
Han Gao, Luning Sun, Jian-Xun Wang
High-resolution (HR) information of fluid flows, although preferable, is usually less accessible due to limited computational or experimental resources. In many cases, fluid data a…
A deep-learning based generalized reduced-order model of glottal flow during normal phonation
Yang Zhang, Weili Jiang, Luning Sun +5
This paper proposes a deep-learning based generalized reduced-order model (ROM) that can provide a fast and accurate prediction of the glottal flow during normal phonation. The app…
Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data
Luning Sun, Jian-Xun Wang
In many applications, flow measurements are usually sparse and possibly noisy. The reconstruction of a high-resolution flow field from limited and imperfect flow information is sig…