Lectures related to Nonlinear Analysis of Structures

Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.

Explores methods for solving non-linear ODE systems and discusses stability conditions.

Delves into the trade-off between model complexity and risk, generalization bounds, and the dangers of overfitting complex function classes.

Explores generalization in deep learning, covering model complexity, implicit bias, and the double descent phenomenon.

Covers the progressive Euler method for numerical integration of ODEs, including Cauchy problems and Runge-Kutta methods.

Covers multistep methods for solving differential equations, focusing on stability conditions and examples.

Explores digital integration methods, stability, and implicit schemes in Runge-Kutta methods.

Covers the stages of the explicit Runge-Kutta method for approximating y(t) with detailed explanations.