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Lecture
Probability Distribution and Entropy
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Entropy in Neuroscience and Ecology
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.
Entropy and Mutual Information
On entropy and mutual information explores quantifying information in data science through probability distributions.
Energy Minimization in Biological Systems: Equilibrium Models
Covers energy minimization models in biological systems, focusing on equilibrium and the roles of entropy and hydrophobicity.
Random Variables and Information Theory Concepts
Introduces random variables and their significance in information theory, covering concepts like expected value and Shannon's entropy.
Random Walks and Moran Model in Population Genetics
Explores random walks, Moran model, bacterial chemotaxis, entropy, information theory, and coevolving sites in proteins.
Lecture: Shannon
Covers the basics of information theory, focusing on Shannon's setting and channel transmission.
Information Theory: Review and Mutual Information
Reviews information measures like entropy and introduces mutual information as a measure of information between random variables.
Information Theory: Entropy and Information Processing
Explores entropy in information theory and its role in data processing and probability distributions.
Mutual Information: Understanding Random Variables
Explores mutual information, quantifying relationships between random variables and measuring information gain and statistical dependence.
