Energy Dissipation Preserving Feature-based DNN Galerkin Methods for Gradient Flows

Documents similaires

• Structured First-Layer Initialization Pre-Training Techniques to Accelerate Training Process Based on $\varepsilon$-Rank
  par: Tang, Tao, et autres
  Publié: (2025)
• $ε$-rank and the Staircase Phenomenon: New Insights into Neural Network Training Dynamics
  par: Yang, Jiang, et autres
  Publié: (2024)
• A Conservative and Positivity-Preserving Discontinuous Galerkin Method for the Population Balance Equation
  par: Xu, Ziyao, et autres
  Publié: (2025)
• Structure Preserving Polytopal Discontinuous Galerkin Methods for the Numerical Modeling of Neurodegenerative Diseases
  par: Corti, Mattia, et autres
  Publié: (2023)
• Higher-Order Energy-Decreasing Exponential Time Differencing Runge-Kutta methods for Gradient Flows
  par: Fu, Zhaohui, et autres
  Publié: (2024)