Correcting model misspecification in physics-informed neural networks (PINNs)
Data-driven discovery of governing equations in computational science has emerged as a
new paradigm for obtaining accurate physical models and as a possible alternative to …
new paradigm for obtaining accurate physical models and as a possible alternative to …
Deep learning for model correction of dynamical systems with data scarcity
C Tatsuoka, D Xiu - arXiv preprint arXiv:2410.17913, 2024 - arxiv.org
We present a deep learning framework for correcting existing dynamical system models
utilizing only a scarce high-fidelity data set. In many practical situations, one has a low …
utilizing only a scarce high-fidelity data set. In many practical situations, one has a low …