3 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.LG2022★ 1 cited
Non-Intrusive Reduced Models based on Operator Inference for Chaotic Systems
João Lucas de Sousa Almeida, Arthur Cancellieri Pires, Klaus Feine Vaz Cid +1
This work explores the physics-driven machine learning technique Operator Inference (OpInf) for predicting the state of chaotic dynamical systems. OpInf provides a non-intrusive ap…
physics.ao-ph2021★ 3 cited
Reduced order modeling of dynamical systems using artificial neural networks applied to water circulation
Alberto Costa Nogueira, João Lucas de Sousa Almeida, Guillaume Auger +1
General circulation models are essential tools in weather and hydrodynamic simulation. They solve discretized, complex physical equations in order to compute evolutionary states of…