Information Measures

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Related lectures (31)

Page 2 of 4

Delves into entropy in neuroscience data and ecology, exploring the representation of sensory information and the diversity of biological populations.

Entropy and Data Compression: Huffman Coding Techniques

Discusses entropy, data compression, and Huffman coding techniques, emphasizing their applications in optimizing codeword lengths and understanding conditional entropy.

Mutual Information and Entropy

Explores mutual information and entropy calculation between random variables.

Generalization Error

Discusses mutual information, data processing inequality, and properties related to leakage in discrete systems.

Source Coding Theorems: Entropy and Source Models

Covers source coding theorems, entropy, and various source models in information theory.

Probability Distribution and Entropy

Explains probability distribution, entropy, and Gibbs free entropy, along with the Weiss model.

Mutual Information in Biological Data

Explores mutual information in biological data, emphasizing its role in quantifying statistical dependence and analyzing protein sequences.

Entropy and KL Divergence

Explores entropy, KL divergence, and maximum entropy principle in probability models for data science.

Random Walks and Moran Model in Population Genetics

Explores random walks, Moran model, bacterial chemotaxis, entropy, information theory, and coevolving sites in proteins.

Random Variables and Information Theory Concepts

Introduces random variables and their significance in information theory, covering concepts like expected value and Shannon's entropy.