MAT 280 Harmonic Analysis on Graphs & Networks Reference Page (Fall 2019)


The general introductory references
  • For general introduction to graphs and networks and significant applications:
  • For Laplacians on graphs:
  • For Laplacians on Euclidean domains:
  • For Laplacians on Riemannian manifolds:
  • For Graph Signal Processing:
  • For Spectral Clustering:

  • Lecture 1: Overture: Why Graphs & Networks? Our Course Plan
    Lecture 2: Prelude to Harmonic Analysis on Graphs: Laplacian Eigenfunctions on General Shape Domains in Rd
    Lecture 3: Basics of Graph Theory: Graph Laplacians
    Lecture 4: Graph Laplacian Eigenvalues
    Lecture 5: Graph Laplacian Eigenvalues II
    Lecture 6: Graph Laplacian Eigenfunctions
    Lecture 7: Graph Laplacian Eigenfunctions II: Spectral Clustering
    Lecture 8: Graph Laplacian Eigenfunctions III: Analysis of Localization/Phase Transition Phenomena
    Lecture 9: Graph Construction from Given Datasets
    Lecture 10: Distances on Graphs
    Lecture 11: Distances on Graphs II: Applications of Commute-Time Distances
    Lecture 12: Applications of Sparse Graphs: Signal Classification Using Sparse Representation
    Lecture 13: Distances on Graphs III: From Commute-Time Distance to Diffusion Distance
    Lecture 14: Dimension Reduction via PCA, Laplacian Eigenmaps, & Diffusion Maps
    Lecture 15: Applications of Dimension Reduction Techniques to Signal Ensemble Classification
    Lecture 16: Wavelets on Graphs I
    Lectures 17/18: Wavelets on Graphs II/III: Organizing `Dual' Domains of Graphs
    Lecture 19: Wavelets on Graphs IV: Hierarchical Graph Laplacian Eigen Transform (HGLET)
    Lecture 20: Wavelets on Graphs V: Generalized Haar-Walsh Transform (GHWT) and its extension eGHWT

    Please email me if you have any comments or questions!
    Go back to MAT 280: Harmonic Analysis on Graphs & Networks Home Page