2 citations · 2 across the 8 of their papers we have counts for
3 papers · 1 filter
Alternating Levenberg-Marquardt Training of Physics-Informed Neural Networks with Fourier-Enhanced Features
Yulun Wu, Matthieu Barreau, Miguel Aguiar +1
Physics-informed neural networks (PINNs) often fail to accurately resolve partial differential equations (PDEs) with high-frequency or multi-scale solutions, as well as strongly no…
Locally Stable Neural ODEs with Characterized Region of Attraction
Alice Harting, Karl Henrik Johansson, Sophie Tarbouriech +1
We propose a class of neural ODEs that universally approximates locally exponentially stable dynamics and the region of attraction from trajectory data. The model dynamics are cons…
RHYME-XT: A Neural Operator for Spatiotemporal Control Systems
Marijn Ruiter, Miguel Aguiar, Jake Rap +2
We propose RHYME-XT, an operator-learning framework for surrogate modeling of spatiotemporal control systems governed by input-affine nonlinear partial integro-differential equatio…