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