Graphs Basics

Medical University of Vienna, Center for Brain Research (Apr 11th 2024)

Here are the materials from the lecture:

  1. Google Slides
  2. Google Colab

And here are additional materials that might be useful to understand the topic:

  1. Spectral and Algebraic Graph Theory by Daniel A. Spielman (textbook) — introduction to the topic, might be too much
  2. Modularity definition (lecture slides) — more detailed explanation of modularity measure
  3. From Louvain to Leiden: guaranteeing well-connected communities (paper) — Leiden algorithm for community detection
  4. Graph drawing by force-directed placement (paper) — Force-directed graphs layouts
  5. How UMAP works? (instruction) — highly recommended, UMAP algrotihm clearly explained
  6. Attraction-Repulsion Spectrum in Neighbor Embeddings (paper) — Cool generalization of t-SNE
  7. Introduction to graph Laplacian (lecture note) — highly recommended, intuitive introduction to graphs Laplacian
  8. Matrix exponential and differential equations (video) — highly recommended, what does e to the power of matrix mean?
  9. Fourier Transform visual introduction (video) — highly recommended, the same for Fourier transform
  10. Wavelets (video) — from Fourier transform to wavelets
  11. Graph Fourier transform (lecture note) — introduction to graphs signal processing
  12. The Emerging Field of Signal Processing on Graphs (paper) — main tricks with graph fourier transform
  13. Distributed harmonic patterns of structure-function dependence orchestrate human consciousness (paper) — graph harmonics and connectomics together