A Dynamics-Informed Gaussian Process Framework for 2D Stochastic Navier-Stokes via Quasi-Gaussianity

Documenti analoghi

• Kernel Methods for Stochastic Dynamical Systems with Application to Koopman Eigenfunctions: Feynman-Kac Representations and RKHS Approximation
  di: Hamzi, Boumediene, et al.
  Pubblicazione: (2026)
• Kernel Methods for Some Transport Equations with Application to Learning Kernels for the Approximation of Koopman Eigenfunctions: A Unified Approach via Variational Methods, Green's Functions and the Method of Characteristics
  di: Hamzi, Boumediene, et al.
  Pubblicazione: (2026)
• Gaussian Processes simplify differential equations
  di: Lee, Jonghyeon, et al.
  Pubblicazione: (2024)
• Kernel Sum of Squares for Data Adapted Kernel Learning of Dynamical Systems from Data: A global optimization approach
  di: Lengyel, Daniel, et al.
  Pubblicazione: (2024)
• Adaptive Kernel Selection for Kernelized Diffusion Maps
  di: Aboussaad, Othmane, et al.
  Pubblicazione: (2026)