A unified physics-informed generative operator framework for general inverse problems

Documenti analoghi

• Weak neural variational inference for solving Bayesian inverse problems without forward models: applications in elastography
  di: Scholz, Vincent C., et al.
  Pubblicazione: (2024)
• DGenNO: A Novel Physics-aware Neural Operator for Solving Forward and Inverse PDE Problems based on Deep, Generative Probabilistic Modeling
  di: Zang, Yaohua, et al.
  Pubblicazione: (2025)
• An effective physics-informed neural operator framework for predicting wavefields
  di: Ma, Xiao, et al.
  Pubblicazione: (2025)
• A variational inference framework for inverse problems
  di: Maestrini, Luca, et al.
  Pubblicazione: (2021)
• A unified framework for geometry-independent operator learning in cardiac electrophysiology simulations
  di: Zhou, Bei, et al.
  Pubblicazione: (2025)