Stochastic Block Model

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (58)

Statistical analysis of network data Log in to Mediaspace to watch this video

Covers stochastic properties, network structures, models, statistics, centrality measures, and sampling methods in network data analysis.

Graph Theory: Girth and Independence Log in to Mediaspace to watch this video

Covers girth, independence, probability, union bound, sets, and hypergraph recoloring.

Convergence of Random Walks Log in to Mediaspace to watch this video

Explores the convergence of random walks on graphs and the properties of weighted adjacency matrices.

Cheeger's Inequalities Log in to Mediaspace to watch this video

Explores Cheeger's inequalities for random walks on graphs and their implications.

Probability & Stochastic Processes Log in to Mediaspace to watch this video

Covers applied probability, stochastic processes, Markov chains, rejection sampling, and Bayesian inference methods.

Maximum Likelihood Theory & Applications Log in to Mediaspace to watch this video

Covers maximum likelihood theory, applications, and hypothesis testing principles in econometrics.

Distances and Motif Counts Log in to Mediaspace to watch this video

Explores distances on graphs, cut norms, spanning trees, blockmodels, metrics, norms, and ERGMs in network data analysis.

Sparsest Cut: Leighton-Rao Algorithm Log in to Mediaspace to watch this video

Covers the Leighton-Rao algorithm for finding the sparsest cut in a graph, focusing on its steps and theoretical foundations.

Sparsest Cut: ARV Theorem Log in to Mediaspace to watch this video

Covers the proof of the Bourgain's ARV Theorem, focusing on the finite set of points in a semi-metric space and the application of the ARV algorithm to find the sparsest cut in a graph.

Gaussian Mixture Models & Noisy Signals Log in to Mediaspace to watch this video

Explores Gaussian mixture models and denoising noisy signals using a probabilistic approach.

Reformulating Problems: Tools and Intuition Log in to Mediaspace to watch this video

Focuses on open problems and the importance of reformulating problems with better tools and intuition.

Pseudorandomness: Expander Mixing Lemma Log in to Mediaspace to watch this video

Explores pseudorandomness and the Expander Mixing Lemma in the context of d-regular graphs.

Interlacing Families and Ramanujan Graphs Log in to Mediaspace to watch this video

Explores interlacing families, Ramanujan graphs, and their construction using signed adjacency matrices.

Linearity of Expectation Log in to Mediaspace to watch this video

Covers Linearity of Expectation, Markov's inequality, random variables, and transitive tournaments.

Isogenic Graphs: Spectral Analysis and Mathematical Applications Log in to Mediaspace to watch this video

Explores isogenic graphs, spectral properties, and mathematical applications in modular forms and cryptography.

Cheeger's Inequality Log in to Mediaspace to watch this video

Explores Cheeger's inequality and its implications in graph theory.

Building Ramanujan Graphs Log in to Mediaspace to watch this video

Explores the construction of Ramanujan graphs using polynomials and addresses challenges with the probabilistic method.

Connectivity-Informed Brain Activity Interpretation Log in to Mediaspace to watch this video

Explores integrating brain connectivity to decode and interpret brain activity using graph signal processing and spectral residual networks.

Graph Theory Fundamentals Log in to Mediaspace to watch this video

Explores fundamental graph theory concepts, Erdős' results, Chromatic Lemma, and Union Bound theorem in graph theory.

Bellman Ford Algorithm Log in to Mediaspace to watch this video

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

Page 2 of 3