Related lectures (27)
Inference Problems & Spin Glass Game
Covers inference problems related to the Spin Glass Game and the challenges of making mistakes with preb P.
Linear Regression: Regularization
Covers linear regression, regularization, and probabilistic models in generating labels.
Statistical Inference: Exponential Families and Likelihoods
Explores exponential families, likelihood functions, and model regularity in statistical inference.
Expectation Maximization and Clustering
Covers the Expectation Maximization algorithm and clustering techniques, focusing on Gibbs Sampling and detailed balance.
Bayesian Inference: Estimation & Demystification
Covers the concepts of Demystification, Estimation, and Bayesian Inference in the context of Bayesian statistics.
Random Walks and Moran Model in Population Genetics
Explores random walks, Moran model, bacterial chemotaxis, entropy, information theory, and coevolving sites in proteins.
Maximum Likelihood Estimation
Covers Maximum Likelihood Estimation in statistical inference, discussing MLE properties, examples, and uniqueness in exponential families.
Estimation & Bayesian Inference
Covers demousing, estimation, Bayesian inference, likelihood, AWGN, and more.
Topic Models: Latent Dirichlet Allocation
Introduces Latent Dirichlet Allocation for topic modeling in documents, discussing its process, applications, and limitations.
Maximum Likelihood: Inference and Model Comparison
Explores maximum likelihood inference, model selection, and comparing models using likelihood ratios.

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