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This 48-minute lecture from the Instituto de Física Interdisciplinar y Sistemas Complejos (IFISC) explores information-theoretic approaches to higher-order Markov processes, covering both theoretical foundations and practical applications. Delve into advanced mathematical frameworks that extend beyond traditional Markov models to capture complex sequential dependencies in various systems. Learn how information theory provides powerful tools for analyzing and modeling higher-order stochastic processes, with demonstrations of real-world applications across scientific disciplines.
