Lectures related to Causal Inference: Front Door Criterion

Flow Networks: Understanding Flows and Cuts in Algorithms

Covers flow networks, focusing on flows, cuts, and their applications in algorithms.

Causal Inference: Understanding Treatment Effects

Explores treatment effects, confounding variables, and challenges in interpreting observational study results.

Explores dynamic programming for the Knapsack problem, discussing strategies, algorithms, NP-hardness, and time complexity analysis.

Graph Algorithms II: Traversal and Paths

Explores graph traversal methods, spanning trees, and shortest paths using BFS and DFS.

Bellman Ford Algorithm

Explores the Bellman Ford algorithm for finding the shortest path in graphs with negative edge weights.

Algorithmic Paradigms for Dynamic Graph Problems

Covers algorithmic paradigms for dynamic graph problems, including dynamic connectivity, expander decomposition, and local clustering, breaking barriers in k-vertex connectivity problems.