Course Recordings

Recordings



  • Lecture 19: Fiedler's Thm and Generalized Laplacian's
  • Lecture 20: Eigenvalues and Vectors by Iterative Methods
  • Lecture 23: Solving Graph Laplacians in Nearly O(m log n) time
  • Lecture 24: Solving Graph Laplacians in Nearly O(m log n) time
  • Lecture 25: Random Walks with Restarts and Spilling Paint
  • Lecture 26: Solving Symmetric Diagonally Dominate
  • Lecture 27: Counting Random Trees
  • Lecture 28: The Markov Chain Tree Theorem
  • Lecture 29: Generating Random Trees
  • Lecture 30: Random Walks and Matching
  • Lecture 31: Graph Neural Networks
  • Lecture 32: Backpropagation
  • Lecture 33: Graph neural network model
  • Lecture 34: Maximum Flow via Electrical Flow