Lecture
Estimation & Bayesian Inference
Related lectures (104)
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Covers entropic notions in quantum sources, Shannon entropy, Von Neumann entropy, and source coding.
Bayesian Inference: Optimal Estimation
Explores optimal Bayesian inference, denoising, scalar estimation, and phase transitions.
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Explores probabilistic linear regression, covering joint and conditional probability, ridge regression, and overfitting mitigation.
Quantum Information
Explores the CHSH operator, self-testing, eigenstates, and quantifying randomness in quantum systems.
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Covers inference problems related to the Spin Glass Game and the challenges of making mistakes with preb P.
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Explores independence and conditional probability in probability and statistics, with examples illustrating the concepts and practical applications.
Generalization Error
Explores tail bounds, information bounds, and maximal leakage in the context of generalization error.
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Covers conditional probability distributions and introduces the concept of conditional expected value.