Networks: Computer Representation

Related lectures (29)

Page 3 of 3

Explores pseudorandomness and the Expander Mixing Lemma in the context of d-regular graphs.

Explores the Laplacian matrix, time-varying consensus theorems, and balanced graphs in networked control systems.

Explores the application of matrices and eigendecompositions in networks.

Explores isogenic graphs, spectral properties, and mathematical applications in modular forms and cryptography.

Explores graphs and matrices, including adjacency, degree, and Laplace matrices, Matrix-tree theorem, and spanning trees.

Introduces the basics of graphs and networks, covering definitions, paths, trees, flows, circulation, and spanning trees.

Explores pseudo randomness in graphs using eigenvalues and polynomials, emphasizing the significance of bunched roots and common interlacers.

Explores consensus in networked control systems through graph weight design and matrix properties.

Explores isogeny graphs of supersingular elliptic curves, showing optimal mixing times for random walks and applications to cryptography.