Learning Lagrangian Fluid Mechanics with E($3$)-Equivariant Graph Neural
Networks

Learning Lagrangian Fluid Mechanics with E( $3$ )-Equivariant Graph Neural Networks

24 May 2023

Artur P. Toshev

Gianluca Galletti

Johannes Brandstetter

Stefan Adami

Nikolaus A. Adams

Papers citing "Learning Lagrangian Fluid Mechanics with E($3$)-Equivariant Graph Neural Networks"

8 / 8 papers shown

Title
JAX-SPH: A Differentiable Smoothed Particle Hydrodynamics Framework Artur P. Toshev Harish D. Ramachandran Jonas A. Erbesdobler Gianluca Galletti Johannes Brandstetter Nikolaus A. Adams 46 7 0 07 Mar 2024
Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators Benedikt Alkin Andreas Fürst Simon Schmid Lukas Gruber Markus Holzleitner Johannes Brandstetter PINN AI4CE 48 8 0 19 Feb 2024
Neural SPH: Improved Neural Modeling of Lagrangian Fluid Dynamics Artur P. Toshev Jonas A. Erbesdobler Nikolaus A. Adams Johannes Brandstetter AI4CE 46 4 0 09 Feb 2024
LagrangeBench: A Lagrangian Fluid Mechanics Benchmarking Suite Stefania Costantini Gianluca Galletti Fabian Fritz Stefan Adami Nikolaus A. Adams 40 13 0 28 Sep 2023
Towards Multi-spatiotemporal-scale Generalized PDE Modeling Jayesh K. Gupta Johannes Brandstetter AI4CE 61 119 0 30 Sep 2022
Clifford Neural Layers for PDE Modeling Johannes Brandstetter Rianne van den Berg Max Welling Jayesh K. Gupta AI4CE 62 81 0 08 Sep 2022
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials Simon L. Batzner Albert Musaelian Lixin Sun Mario Geiger J. Mailoa M. Kornbluth N. Molinari Tess E. Smidt Boris Kozinsky 233 1,240 0 08 Jan 2021
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 238 2,298 0 18 Oct 2020