We use the method of Maximum (relative) Entropy to process information in the form of observed data and moment constraints, when they should be processed sequentially and when simultaneously.Expand

We show that Skilling's method of induction leads to a unique general theory of inductive inference, the method of Maximum relative Entropy; other entropies such as those of Renyi or Tsallis are ruled out.Expand

In this thesis we start by providing some detail regarding how we arrived at our present understanding of probabilities and how we manipulate them - the product and addition rules by Cox.Expand

Jadomycins are novel antibiotics that exhibit biological activity against bacteria and yeast and also demonstrate cytotoxicity against cancer cells. Jadomycin C was successfully produced from 10 L of… Expand

In this article, we investigate the possibility of describing the macroscopic behavior of complex systems in terms of the underlying statistical structure of their microscopic degrees of freedom by use of statistical inductive inference and information geometry.Expand

Abstract A general probabilistic inference procedure is proposed in this paper based on the Maximum relative Entropy (MrE) approach which generalizes both Bayesian and Maximum Entropy (MaxEnt)… Expand

From the Horowitz-Esposito stochastic thermodynamical description of information flows in dynamical systems [J. M. Horowitz and M. Esposito, Phys. Rev. X 4, 031015 (2014)], it is known that while the… Expand

We present a differential geometric viewpoint of the quantum MaxEnt estimate of a density operator when only incomplete knowledge encoded in the expectation values of a set of quantum observables is… Expand

For over 25 years the MaxEnt workshops have explored the use of Bayesian probability theory, entropy and information theory in scientific and engineering applications.Expand