Resources đ
- CS224W: Machine Learning with Graphs taught by Jurij Leskovec
- Network Analysis and Modeling CSCI 5352 (Fall 2017) by Aaron Clauset
- Network Science by Albert-LĂĄszlĂł BarabĂĄsi
- Graph Representation Learning by William L. Hamilton
- Glossary of graph theory - Wikipedia
Concepts
- Reducible Matrix â from Wolfram MathWorld - defn from Wolfram states the inverse of irreducibility
- see also Matrix irreducibility. Strongly connected graph - there is an obvious connection between reducible matrices, representing graphs (adjacency matrices) and strongly connected graphs: obviously if a graph has a connection between all nodes (not necessarily direct between any two given nodes, but rather via a path), i.e. is strongly connected, we will have irreducibility of the random walk (Markov chain) induced by that graph
- See also Bayesian Statistics & Stochastic Processes and Watermarks in the Sand Impossibility of Strong Watermarking for Generative Models
- Path (graph theory) - Wikipedia