yellowshippo/penn-neurips2022
PENN code for NeurIPS 2022
This project offers a method for scientists and engineers to solve complex physics problems using neural networks. It takes data representing physical systems (like fluid flows or diffusion processes) and boundary conditions as input, then generates predictions for how these systems behave. This is particularly useful for researchers in fields like computational fluid dynamics or materials science who need to simulate physical phenomena.
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Use this if you need to simulate partial differential equations (PDEs) for physical systems, especially those with mixed boundary conditions, and want to leverage graph neural networks for faster or more accurate solutions than traditional methods.
Not ideal if you are not working with physics-based simulations or do not have access to GPU hardware, as the project requires specific computational resources.
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42
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5
Language
Python
License
Apache-2.0
Category
Last pushed
Jan 11, 2023
Commits (30d)
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