Login to filter by course Login to filter by course Reset
Explores the benefits of deeper networks in deep learning and the importance of over-parameterization and generalization.
Covers the Finite Element Method, discussing the derivation of the equation of motion and exploring mass and stiffness matrices.
Covers the derivation of the equation of motion, interpolation, Newton's equation, and energy conservation in finite element modeling.
Explores interpolation of regular functions, error analysis, convergence, and Chebyshev polynomials.
Covers the fundamentals of finite element analysis, including traction and interpolation functions.
Covers the concept of rigid displacement and potential energy, emphasizing continuity between elements and the importance of conforming to the mesh.
Discusses deterministic interpolation methods, comparing global and local approaches for predicting spatial distributions.
Explores interpolation spaces between Banach spaces and real interpolation spaces.
