AI4Science-WestlakeU/safediffcon

[ICML2025] SafeDiffCon is a diffusion model for safe PDE Control.

27
/ 100
Experimental

This project helps scientists and engineers working with complex physical systems to design controllers that are safe and reliable. It takes data describing a physical system's behavior, like fluid dynamics or plasma confinement (PDEs), and provides optimized control strategies that ensure the system operates within safety limits. Researchers in fields like aerospace, energy, or materials science who need to precisely manage dynamic processes under uncertainty would find this useful.

Use this if you are developing control systems for physical phenomena modeled by Partial Differential Equations (PDEs) and need to guarantee safety constraints are always met, especially when dealing with inherent system uncertainties.

Not ideal if your control task does not involve PDEs, or if safety under uncertainty is not a critical concern for your application.

physical-system-control PDE-modeling safety-critical-systems uncertainty-quantification engineering-design
No Package No Dependents
Maintenance 6 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 0 / 25

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Stars

12

Forks

Language

Python

License

MIT

Last pushed

Oct 19, 2025

Commits (30d)

0

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