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Importance of equivariant and invariant symmetries for fluid flow
  modeling

Importance of equivariant and invariant symmetries for fluid flow modeling

3 May 2023
Varun Shankar
Shivam Barwey
Zico Kolter
R. Maulik
V. Viswanathan
    AI4CE
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
1