Optimization problems and their solution by symbolic regression methods are considered. The search is performed on non-Euclidean space. In such spaces it impossible to determine a distance between two potential solutions and, therefore, algorithms using arithmetic operations of multiplication addition not used there. optimal the space codes. It proposed that principle small variations basic be ...

We propose several approaches for solving regression problems and differential equations (DEs) with quantum kernel methods. compose models as weighted sums of functions, where variables are encoded using feature maps model derivatives represented automatic differentiation circuits. While previously methods primarily targeted classification tasks, here we consider their applicability to based on...