Academic
Scientific Computing with GANs and VAEs
Research seminar project on generative models as surrogate models for solving complex partial differential equations.
GANsVAEsScientific ComputingPDEsResearch
Overview
This seminar project investigated generative models as surrogate models for complex partial differential equations.
Project scope
As part of the seminar, we investigated how generative models can be used as surrogate models for complex partial differential equations.
The work covered:
- GANs and VAEs as generative modeling approaches
- surrogate modeling for expensive scientific simulations
- trade-offs between approximation quality, training complexity, and practical usefulness
- writing the results as a seminar paper