Scientific machine learning for closure models in multiscale problems: A review
Closure problems are omnipresent when simulating multiscale systems, where some
quantities and processes cannot be fully prescribed despite their effects on the simulation's …
quantities and processes cannot be fully prescribed despite their effects on the simulation's …
Mesh-based Super-Resolution of Fluid Flows with Multiscale Graph Neural Networks
A graph neural network (GNN) approach is introduced in this work which enables mesh-
based three-dimensional super-resolution of fluid flows. In this framework, the GNN is …
based three-dimensional super-resolution of fluid flows. In this framework, the GNN is …
SE (3)-Equivariant Diffusion Graph Nets: Synthesizing Flow Fields by Denoising Invariant Latents on Graphs
We introduce SE (3)-equivariant diffusion graph nets (SE3-DGNs) for generating physical
fields on graphs. SE3-DGNs integrate a SE (3)-equivariant variational graph autoencoder …
fields on graphs. SE3-DGNs integrate a SE (3)-equivariant variational graph autoencoder …
Hierarchical equivariant graph neural networks for forecasting collective motion in vortex clusters and microswimmers
Data-driven modeling of collective dynamics is a challenging problem because emergent
phenomena in multi-agent systems are often shaped by long-range interactions among …
phenomena in multi-agent systems are often shaped by long-range interactions among …
Scalable and Consistent Graph Neural Networks for Distributed Mesh-based Data-driven Modeling
This work develops a distributed graph neural network (GNN) methodology for mesh-based
modeling applications using a consistent neural message passing layer. As the name …
modeling applications using a consistent neural message passing layer. As the name …
Machine learning applications in astrophysics: Reduced-order modelling for chemical kinetics and galaxy merger reconstruction with graph neural network
KS Tang - 2024 - ideals.illinois.edu
This thesis explores the application of deep learning techniques to two astrophysical
problems: simplifying chemical kinetics calculations and reconstructing galaxy merger …
problems: simplifying chemical kinetics calculations and reconstructing galaxy merger …