31 citations · 59 across the 5 of their papers we have counts for
5 papers
-HIGNN: A Scalable Graph Neural Network Framework with Hierarchical Matrix Acceleration for Simulation of Large-Scale Particulate Suspensions
Zhan Ma, Zisheng Ye, Ebrahim Safdarian +1
We present a fast and scalable framework, leveraging graph neural networks (GNNs) and hierarchical matrix (-matrix) techniques, for simulating large-scale particulate…
Fast Simulation of Particulate Suspensions Enabled by Graph Neural Network
Zhan Ma, Zisheng Ye, Wenxiao Pan
Predicting the dynamic behaviors of particles in suspension subject to hydrodynamic interaction (HI) and external drive can be critical for many applications. By harvesting advance…
Data-driven Coarse-grained Modeling of Non-equilibrium Systems
Shu Wang, Zhan Ma, Wenxiao Pan
Modeling a high-dimensional Hamiltonian system in reduced dimensions with respect to coarse-grained (CG) variables can greatly reduce computational cost and enable efficient bottom…
Transfer Learning of Memory Kernels in Coarse-grained Modeling
Zhan Ma, Shu Wang, Minhee Kim +3
The present work concerns the transferability of coarse-grained (CG) modeling in reproducing the dynamic properties of the reference atomistic systems across a range of parameters.…
Data-driven nonintrusive reduced order modeling for dynamical systems with moving boundaries using Gaussian process regression
Zhan Ma, Wenxiao Pan
We present a data-driven nonintrusive model order reduction method for dynamical systems with moving boundaries. The proposed method draws on the proper orthogonal decomposition, G…