Our paper on physics-constrained reconstruction / super-resolution with generative models was posted online now at https://doi.org/10.1063/5.0304492
This paper started out as a master thesis by Marc Trepat, was continued with Luis‘ thesis, and turned out to work exceptionally well:
- PDE Transformer as an accurate & efficient backbone architecture https://tum-pbs.github.io/pde-transformer/landing.html
- Differentiable physics constraints to guide the generative model https://ge.in.tum.de/publications/2020-um-solver-in-the-loop/
- and ConFIG as optimizer to resolve conflicts in the gradients https://tum-pbs.github.io/ConFIG/
Source code is available at https://github.com/tum-pbs/sparse-reconstruction , let us know how it works for you.
