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Delves into uniformly accurate hydrodynamic models for kinetic equations using machine learning, covering Boltzmann equation, moment methods, and numerical results.
Delves into quantifying entropy in neuroscience data, exploring how neuron activity represents sensory information and the implications of binary digit sequences.
Explores chemical equilibrium principles, including Le Châtelier's Principle and equilibrium constants, and discusses the influence of temperature, pressure, and concentration on equilibrium shifts.
Covers Markov processes, transition densities, and distribution conditional on information, discussing classification of states and stationary distributions.
