Cross-entropy

Related lectures (32)

Explores mutual information and entropy calculation between random variables.

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

Covers energy minimization models in biological systems, focusing on equilibrium and the roles of entropy and hydrophobicity.

Covers the basics of information theory, focusing on Shannon's setting and channel transmission.

Explores conditional entropy and Huffman coding for efficient data compression techniques.

Explores entropy in thermodynamics, including Gibbs equations, ideal gases, and entropy balance in closed systems.

Delves into interpreting neural network output as probabilities based on the cross-entropy error function.

Explores entropy, randomness, and information quantification in biological data analysis, including neuroscience and protein structure prediction.

Covers classification problems and various loss functions used in machine learning.

Introduces information theory basics, including entropy, independence, and binary entropy function.

Explores a first-order Markov model using a sunny-rainy source example, demonstrating how past events influence future outcomes.

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

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