Physics-Informed Neural Network Frameworks for the Analysis of Engineering and Biological Dynamical Systems Governed by Ordinary Differential Equations

Ähnliche Einträge

• PBPK-iPINNs: Inverse Physics-Informed Neural Networks for Physiologically Based Pharmacokinetic Brain Models
  von: Wickramasinghe, Charuka D., et al.
  Veröffentlicht: (2025)
• A Graded Mesh Refinement for 2D Poisson's Equation on Non Convex Polygonal Domains
  von: Wickramasinghe, Charuka D., et al.
  Veröffentlicht: (2024)
• Invariant Physics-Informed Neural Networks for Ordinary Differential Equations
  von: Arora, Shivam, et al.
  Veröffentlicht: (2023)
• TumorPred: A Computational Framework Implemented via an R/Shiny Web Application for Parameter Estimation and Sensitivity Analysis in Compartmental Brain Modeling
  von: Wickramasinghe, Charuka D., et al.
  Veröffentlicht: (2025)
• Accelerating the Simulation of Ordinary Differential Equations Through Physics-Preserving Neural Networks
  von: Tagg, Andrew, et al.
  Veröffentlicht: (2026)