Covers the Runge Kutta method and its application to optimal control and neural networks.
Covers gradient line search methods and optimization techniques with an emphasis on Wolfe conditions and positive definiteness.
Explores numerical methods for solving ODE systems, stability regions, and absolute stability importance.
Covers advanced numerical analysis topics including deep neural networks and optimization methods.
Covers optimization methods without constraints, including gradient and line search in the quadratic case.
Explores error estimation in numerical methods for solving ordinary differential equations, emphasizing the impact of errors on solution accuracy and stability.
Covers the derivation of the equation of motion, interpolation, Newton's equation, and energy conservation in finite element modeling.
Covers the Finite Element Method, discussing the derivation of the equation of motion and exploring mass and stiffness matrices.
