Cross-Validation of SPH-based Machine Learning Models using the Taylor-Green Vortex Case
Cross-validating SPH-based machine learning models on the Taylor-Green vortex, as a shared reference case.
Machine learning results in fluid mechanics are difficult to compare because everyone evaluates on different data. This paper uses the Taylor-Green vortex as a common reference case for cross-validating SPH-based learned models.
Presented at the Particle Methods and Applications Conference 2024 in Santa Fe, USA.
References
2024
- Cross-Validation of SPH-based Machine Learning Models using the Taylor-Green Vortex CaseIn Particle Methods and Applications Conference, Santa Fe, USA, 2024