Neural Networks and Symbolic Differential Equations

Recent advances in Wolfram Language use neural networks to assist in solving nonlinear ordinary differential equations. This talk presents how machine learning–powered methods integrate with DSolve, enabling solutions in cases where traditional symbolic approaches struggle. We showcase example systems and highlight the hybrid symbolic–numeric approach.