Principles of maximum entropy and maximum caliber in statistical physics

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The statistical physics of real-world networks (2018, background): “The maximum entropy principle is conceptually very powerful and finds almost countless applications in physics and in science in general [29].”
Nonequilibrium physics in biology (2019, background): “We expect that the study of cell signal transduction, neural networks in the brain, and organisms will play a leading role in this endeavor (Bialek, 2012; Levchenko and Nemenman, 2014; Press et al., 2013; Yan et al., 2016; Zeng and Wang, 2017) that has only begun.”
Connecting the Sequence-Space of Bacterial Signaling Proteins to Phenotypes Using Coevolutionary Landscapes (2016, methodology): “Typical approaches to this problem have applied the principle of maximum entropy (See Review: (53)) to infer a least biased model that is consistent with the input sequence data (18, 20), e.”
Inverse statistical problems: from the inverse Ising problem to data science (2017, methodology): “The notion of a steady-state distribution with maximum entropy has been generalized to a maximum-entropy distribution over trajectories of a dynamical sys-tem [167].”