Optimal Transport: Gradient Flows

Related lectures (29)

Page 3 of 3

Explores numerical methods like Crank-Nicolson, Heun, Euler, and RK4 for solving ODEs, emphasizing error estimation and convergence.

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

Explores error analysis in ordinary differential equations and convergence criteria for numerical methods.

Explores the application of randomness in physical models, focusing on Brownian motion and diffusion.

Explores ordinary differential equations and numerical integration methods for stability and accuracy.

Covers the Fourier law, heat equation, Righi-Leduc effect, and related experiments.

Explores methods for ordinary differential equations and the importance of Lipschitz continuity in ensuring unique solutions.

Covers the numerical approximation of PDEs and examples of nonlinear behavior.

Explores the heat equation, equilibrium equations, heat flux, and harmonic functions in heat distribution.