Neural Conjugate Flows: Physics-informed architectures with flow structure

Documenti analoghi

• Physics-informed sensor coverage through structure preserving machine learning
  di: Shaffer, Benjamin David, et al.
  Pubblicazione: (2025)
• Deep NURBS -- Admissible Physics-informed Neural Networks
  di: Saidaoui, Hamed, et al.
  Pubblicazione: (2022)
• Domain decomposition architectures and Gauss-Newton training for physics-informed neural networks
  di: Heinlein, Alexander, et al.
  Pubblicazione: (2025)
• Inverse Evolution Layers: Physics-informed Regularizers for Deep Neural Networks
  di: Liu, Chaoyu, et al.
  Pubblicazione: (2023)
• Learning from Linear Algebra: A Graph Neural Network Approach to Preconditioner Design for Conjugate Gradient Solvers
  di: Trifonov, Vladislav, et al.
  Pubblicazione: (2024)