All Stories

  1. Learning of discrete models of variational PDEs from data
  2. Hamiltonian neural networks with automatic symmetry detection
  3. Efficient Time-Stepping for Numerical Integration Using Reinforcement Learning
  4. Variational learning of Euler–Lagrange dynamics from data
  5. Backward error analysis for conjugate symplectic methods
  6. Learning Discrete Lagrangians for Variational PDEs from Data and Detection of Travelling Waves
  7. Symplectic integration of learned Hamiltonian systems
  8. Backward error analysis for variational discretisations of PDEs
  9. Learning ODE Models with Qualitative Structure Using Gaussian Processes
  10. Bifurcation preserving discretisations of optimal control problems
  11. Detection of high codimensional bifurcations in variational PDEs
  12. Preservation of Bifurcations of Hamiltonian Boundary Value Problems Under Discretisation
  13. Hamiltonian Boundary Value Problems, Conformal Symplectic Symmetries, and Conjugate Loci
  14. Symplectic integration of boundary value problems
  15. Bifurcation of solutions to Hamiltonian boundary value problems
  16. Symplectic integration of PDEs using Clebsch variables