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MIT Subject Listing & Schedule
Fall 2025 Search Results

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1 subject found.

6.7800 Inference and Information
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Graduate (Spring)
Prereq: 6.3700, 6.3800, or 6.7700
Units: 4-0-8
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Introduction to principles of Bayesian and non-Bayesian statistical inference and its information theoretic foundations. Hypothesis testing and parameter estimation, sufficient statistics, exponential families. Loss functions, information measures, model capacity, and information geometry. Variational inference and EM algorithm; MCMC and other Monte Carlo methods. Asymptotic analysis and large deviations theory; universal inference and learning. Selected topics such as representation learning, score-matching, diffusion, and nonparametric statistics.
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