Uncertainty quantification for physics-informed deep learning
The development of physics-informed deep learning is radically changing compu-tational science and engineering, allowing for an effective integration ofphysics-based and datadriven modeling. Deep learning provides a powerful tool forthe discovery of governing dynamics underneath data and enables nonlinear model-reduction. A Bayesian viewpoint of deep learning is discussed in this chapter towards t