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Importance of equivariant and invariant symmetries for fluid flow modeling

Importance of equivariant and invariant symmetries for fluid flow modeling

Varun Shankar
Shivam Barwey
Zico Kolter
R. Maulik
V. Viswanathan
ArXiv (abs)PDFHTML

Papers citing "Importance of equivariant and invariant symmetries for fluid flow modeling"

3 / 3 papers shown
Title
Harnessing Equivariance: Modeling Turbulence with Graph Neural Networks
Harnessing Equivariance: Modeling Turbulence with Graph Neural Networks
Marius Kurz
Andrea Beck
Benjamin Sanderse
AI4CE
72
2
0
10 Apr 2025
Scalable and Consistent Graph Neural Networks for Distributed Mesh-based Data-driven Modeling
Scalable and Consistent Graph Neural Networks for Distributed Mesh-based Data-driven Modeling
Shivam Barwey
Riccardo Balin
Bethany Lusch
Saumil Patel
Ramesh Balakrishnan
Pinaki Pal
R. Maulik
V. Vishwanath
GNNAI4CE
78
1
0
02 Oct 2024
Mesh-based Super-Resolution of Fluid Flows with Multiscale Graph Neural Networks
Mesh-based Super-Resolution of Fluid Flows with Multiscale Graph Neural Networks
Shivam Barwey
Pinaki Pal
Saumil Patel
Riccardo Balin
Bethany Lusch
V. Vishwanath
R. Maulik
R. Balakrishnan
AI4CE
281
1
0
12 Sep 2024

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