Develop Physics-Informed Machine Learning Models with Graph Neural Networks

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Originally published at: https://developer.nvidia.com/blog/develop-physics-informed-machine-learning-models-with-graph-neural-networks/

Modulus 23.05 brings together new capabilities, empowering the research community and industries to develop research into enterprise-grade solutions through open-source collaboration.

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I would love to see if the PyTorch Modulus implementation of Meshgraphnets achieves the same accuracy as the original tensorflow implementation? Are there any public experiment records on how Modulus performed, for e.g. the cylinderflow example?

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Hello, and thanks for your comment! Unfortunately, we do not have any quantitative comparison between the Modulus implementation and the original TF implementation of MeshGraphNet yet.