Benchmarking Neural Surrogates for Complex Simulations
Published:Dec 21, 2025 05:04
•1 min read
•ArXiv
Analysis
This ArXiv paper investigates the performance of neural surrogates in the context of realistic spatiotemporal multiphysics flows, offering a crucial assessment of these models' capabilities. The study provides valuable insights into the strengths and weaknesses of neural surrogates, informing their practical application in scientific computing and engineering.
Key Takeaways
- •Evaluates neural surrogate performance in complex simulations.
- •Provides insights into the applicability of these models.
- •Relevant for researchers and practitioners in computational fields.
Reference
“The study focuses on realistic spatiotemporal multiphysics flows.”