2 papers
cs.LG2023
Learning Dynamical Systems from Noisy Data with Inverse-Explicit Integrators
Håkon Noren, Sølve Eidnes, Elena Celledoni
We introduce the mean inverse integrator (MII), a novel approach to increase the accuracy when training neural networks to approximate vector fields of dynamical systems from noisy…
math.NA2023
Learning Hamiltonian Systems with Mono-Implicit Runge-Kutta Methods
Håkon Noren
Numerical integrators could be used to form interpolation conditions when training neural networks to approximate the vector field of an ordinary differential equation (ODE) from d…