Lectures related to Graph Processing: Oracle Labs PGX

Introduces network data structures, models, and analysis techniques, emphasizing permutation invariance and Erdős-Rényi networks.

Explores real functions, their graphs, properties, and transformations, including symmetry and surjection.

Explores causal inference through learning graph structures for causal reasoning from observational data.

Covers the independence polynomial of a dependency graph and related concepts such as graph coloring and directed graph properties.

Explores Prim's algorithm for minimum spanning trees and introduces the Traveling Salesman Problem.

Explores derivatives, tangents, and elementary function rules in general mathematics.

Delves into graph-enhanced machine learning, focusing on fraud detection, malware detection, and recommendation systems.