Here are the Python codes for the numerical examples in the book chapter " Guofei Pang, George Em Karniadakis (2020). Physics-informed learning machines for PDEs: Gaussian processes versus neural networks. In Panayotis G. Kevrekidis, Avadh B. Saxena andJesus Cuevas-Maraver (Eds.), Nonlinear science: a 20/20 vision. Speringer Nature Switzerland AG. " Using them you can implement physics-infromed Gaussian processes and physics-informed neural networks in solving linear and nonlinear partial differential equations. The codes can handle both forward problem and inverse can

The codes were tested to run on both Linux and Windows. A TensorFlow with version 1.13.1 is required to install.