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Related lectures (31)
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Graph Alignment: Wasserstein-based
Discusses challenges in comparing non-Euclidean data, proposing a Laplacian-based solution for graph alignment and exploring optimal transport for graph distance computation.
Networked Control Systems
Explores networked control systems, covering current injection, Laplacian flow, consensus states, and balanced digraph design.
Process Models & Parameter Identification
Covers calibrating models using measurements, virtual sensors, data reconciliation, and parameter identification in process models.
Matrix Tree Theorem
Explores the Matrix Tree Theorem and its application in calculating spanning trees in graphs.
Networked Control Systems: Properties and Connectivity
Explores properties of matrices, irreducibility, and graph connectivity in networked control systems.
Laplacian Matrix: Properties and Examples
Explores the Laplacian matrix, time-varying consensus theorems, and balanced graphs in networked control systems.
Interlacing Families and Ramanujan Graphs
Explores interlacing families of polynomials and 1-sided Ramanujan graphs, focusing on their properties and construction methods.
Pseudo Randomness in Graphs
Explores pseudo randomness in graphs using eigenvalues and polynomials, emphasizing the significance of bunched roots and common interlacers.
Spectral Clustering: Finding Clusters
Explores Spectral Clustering, eigenvalue decomposition, Laplacian matrices, and cluster identification through eigenvector projections.
Networks: Computer Representation
Covers the concept of adjacency matrix and adjacency lists for representing networks.