60 citations · 121 across the 21 of their papers we have counts for
3 papers · 1 filter
A domain decomposition-based autoregressive deep learning model for unsteady and nonlinear partial differential equations
Sheel Nidhan, Haoliang Jiang, Lalit Ghule +3
In this paper, we propose a domain-decomposition-based deep learning (DL) framework, named transient-CoMLSim, for accurately modeling unsteady and nonlinear partial differential eq…
Fast meta-solvers for 3D complex-shape scatterers using neural operators trained on a non-scattering problem
Youngkyu Lee, Shanqing Liu, Zongren Zou +5
Three-dimensional target identification using scattering techniques requires high accuracy solutions and very fast computations for real-time predictions in some critical applicati…
Sampling-based Distributed Training with Message Passing Neural Network
Priyesh Kakka, Sheel Nidhan, Rishikesh Ranade +2
In this study, we introduce a domain-decomposition-based distributed training and inference approach for message-passing neural networks (MPNN). Our objective is to address the cha…