Concept
Graphical model
Related lectures (38)
Graphical Models: Probability Distributions and Factor Graphs
Covers graphical models for probability distributions and factor graphs representation.
Ensemble Methods: Random Forests
Covers ensemble methods like random forests and Gaussian Naive Bayes, explaining how they improve prediction accuracy and estimate conditional Gaussian distributions.
Algebraic Kunneth Theorem
Covers the Algebraic Kunneth Theorem, explaining chain complexes and cohomology computations.
Segmentation: Theory and Algorithms
Covers the theory and algorithms behind image segmentation, focusing on region identification and evaluation.
Text Models: Word Embeddings and Topic Models
Explores word embeddings, topic models, Word2vec, Bayesian Networks, and inference methods like Gibbs sampling.
Belief Propagation and Survey Propagation
Explores belief propagation, frozen clusters, and colorability thresholds in graphical models, leading to the significance of survey propagation in solving constraint satisfaction problems.
ARCH and GARCH Models
Explores ARCH and GARCH models, volatility clustering, time series, estimation, and filtering steps in financial and macroeconomic contexts.