jhagnberger/calm-pde
[NeurIPS 2025] Official PyTorch implementation of the CALM layers and CALM-PDE model.
CALM-PDE helps scientists and engineers accurately predict how complex physical systems change over time, such as fluid dynamics or heat transfer. You provide initial conditions of a system, like the starting flow around an object, and it outputs the system's evolution over a sequence of future time steps. This tool is designed for researchers in physics, engineering, and scientific computing who work with partial differential equations (PDEs).
Use this if you need to simulate complex, time-dependent physical phenomena governed by partial differential equations and require accurate predictions of system states over time.
Not ideal if your problem does not involve time-dependent PDEs or if you primarily need to analyze static physical properties rather than dynamic evolution.
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Python
License
MIT
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Last pushed
Oct 20, 2025
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