The variational principles called maximum entropy (MaxEnt) and maximum caliber
(MaxCal)<? format?> are reviewed. MaxEnt originated in the statistical physics of Boltzmann …

A cornerstone of statistical inference, the maximum entropy framework is being increasingly
applied to construct descriptive and predictive models of biological systems, especially …

Super-resolution microscopy provides direct insight into fundamental biological processes
occurring at length scales smaller than light's diffraction limit. The analysis of data at such …

Ever since Clausius in 1865 and Boltzmann in 1877, the concepts of entropy and of its
maximization have been the foundations for predicting how material equilibria derive from …

Most natural systems operate far from equilibrium, displaying time-asymmetric, irreversible
dynamics characterized by a positive entropy production while exchanging energy and …

We review here Maximum Caliber (Max Cal), a general variational principle for inferring
distributions of paths in dynamical processes and networks. Max Cal is to dynamical …

Statistical physics relates the properties of macroscale systems to the distributions of their
microscale agents. Its central tool has been the maximization of entropy, an equilibrium …

Recurrent neural networks have seen widespread use in modeling dynamical systems in
varied domains such as weather prediction, text prediction and several others. Often one …

Computational strategies aimed at unveiling the thermodynamic and kinetic properties of G
Protein-Coupled Receptor (GPCR) activation require extensive molecular dynamics …

The ability to distinguish between stochastic systems based on their trajectories is crucial in
thermodynamics, chemistry, and biophysics. The Kullback–Leibler (KL) divergence, D KL AB …