jhagnberger/vcnef
[ICML 2024] Official PyTorch implementation of the Vectorized Conditional Neural Field.
This tool helps scientists and engineers accurately predict how complex systems evolve over time, based on their initial conditions and physical parameters. You input data describing the system's current state and relevant parameters, and it outputs predictions for future states. Researchers in physics, engineering, and climate science who need to simulate dynamic phenomena will find this valuable.
No commits in the last 6 months.
Use this if you need a flexible and efficient way to simulate time-dependent physical processes and predict their behavior, especially when dealing with various spatial dimensions or changing parameters.
Not ideal if your problem does not involve differential equations, or if you require an extremely lightweight solution without deep learning components.
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Language
Python
License
MIT
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Last pushed
Aug 01, 2024
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