Generalization capabilities and robustness of hybrid models grounded in physics compared to purely deep learning models

Documenti analoghi

• Reduced-order modeling of a viscoelastic turbulent jet with hybrid machine learning models
  di: Amor, Christian, et al.
  Pubblicazione: (2026)
• Hybrid machine learning models based on physical patterns to accelerate CFD simulations: a short guide on autoregressive models
  di: Sengupta, Arindam, et al.
  Pubblicazione: (2025)
• An Adaptive Framework for Autoregressive Forecasting in CFD Using Hybrid Modal Decomposition and Deep Learning
  di: Abadía-Heredia, Rodrigo, et al.
  Pubblicazione: (2025)
• Generative artificial intelligence and hybrid models to accelerate LES in reactive flows: Application to hydrogen/methane combustion
  di: Zou, Xiangrui, et al.
  Pubblicazione: (2025)
• LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements
  di: Hetherington, Ashton, et al.
  Pubblicazione: (2024)