gd-gradient-flow-ode

IN premise — entries/2026/06/21/wiki-Gradient_descent-chunk-4.md

Created 2026-06-21T09:55:50+00:00

Gradient descent is Euler's method applied to the ODE x'(t) = -∇f(x(t)), connecting optimization to dynamical systems theory

Dependents

These beliefs depend on this one:

• IN gradient-learning-connects-autodiff-optimization-dynamics — Gradient-based neural network training sits at the intersection of three mathematical frameworks: reverse-mode automatic differentiation (backprop), iterative optimization (gradient descent), and continuous dynamical systems (gradient flow ODE).