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Autor:
Almeida, João Lucas de Sousa, Pires, Arthur Cancellieri, Cid, Klaus Feine Vaz, Junior, Alberto Costa Nogueira
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 approach to infer approximations of polynomial operators in reduced spac
Externí odkaz:
http://arxiv.org/abs/2206.01604
