• Publications
  • Influence
Updating Probabilities with Data and Moments
TLDR
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
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Updating Probabilities
TLDR
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
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Maximum Entropy: The Universal Method for Inference
  • A. Giffin
  • Mathematics, Computer Science
  • 20 January 2009
TLDR
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
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Heat Balance Analysis During the Production of Jadomycin C
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 ofExpand
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Complexity Characterization in a Probabilistic Approach to Dynamical Systems Through Information Geometry and Inductive Inference
TLDR
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
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Maximum relative entropy-based probabilistic inference in fatigue crack damage prognostics
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
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Thermodynamic aspects of information transfer in complex dynamical systems.
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 theExpand
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On a differential geometric viewpoint of Jaynes' MaxEnt method and its quantum extension
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 isExpand
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Bayesian Inference and Maximum Entropy Methods in Science and Engineering: 27th International Workshop on Bayesian Inference and Maximum Entropy Methods
TLDR
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
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The Kalman Filter Revisited Using Maximum Relative Entropy
TLDR
In 1960, Rudolf E. Kalman created what is known as the Kalman filter, which is a way to estimate unknown variables from noisy measurements. Expand
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