Automated design parameter selection for neural networks solving coupled partial differential equations with discontinuities

► Accurately solves discontinuous differential equations using neural networks. ► The approximate solution exactly satisfies boundary conditions even before training. ► Handles coupled systems of nonlinear partial differential equations. ► Automated design parameter selection which is independent of the designer's bias.