Lectures related to Quantifying Information: Probability, Entropy, and Constraints

Explores variational formulation for measuring information content and divergence between probability distributions.

Explores randomness in biology, covering thermal fluctuations, random walks, and data analysis techniques.

Explores nonparametric relationships in GLMs and the importance of understanding variability through probability and models.

Explores stationary sources, entropy, regularity, and coding efficiency, including a challenging problem with billiard balls.

Explores entropy as a measure of disorder and how it can be increased.

Explores independence and conditional probability in probability and statistics, with examples illustrating the concepts and practical applications.

Explores entropy in information theory and its role in data processing and probability distributions.