Covers the interpretation of the Lindblad equation and its unitary part in quantum gases.
Introduces Hidden Markov Models, explaining the basic problems and algorithms like Forward-Backward, Viterbi, and Baum-Welch, with a focus on Expectation-Maximization.
Explores dependence, correlation, and conditional expectations in probability and statistics, highlighting their significance and limitations.
Introduces key concepts in probability and statistics, covering random experiments, events, intersections, unions, and more.
Covers moments, variance, and expected values in probability and statistics, including the distribution of tokens in a product.
