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  • Entropy - MDPI
    The concept of entropy constitutes, together with energy, a cornerstone of contemporary physics and related areas It was originally introduced by Clausius in 1865 along abstract lines focusing on thermodynamical irreversibility of macroscopic physical processes
  • Entropy | An Open Access Journal from MDPI
    Entropy Entropy is an international and interdisciplinary peer-reviewed open access journal of entropy and information studies, published monthly online by MDPI
  • Entropy | Aims Scope - MDPI
    Entropy (ISSN 1099-4300), an international and interdisciplinary journal of entropy and information studies, publishes reviews, regular research papers and short notes
  • Entropy and Time - MDPI
    The idea that entropy is associated with the “arrow of time” has its roots in Clausius’s statement on the Second Law: “Entropy of the Universe always increases ” However, the explicit association of the entropy with time’s arrow arises from Eddington
  • Entropy: From Thermodynamics to Information Processing - MDPI
    Entropy is most commonly defined as “disorder”, although it is not a good analogy since “order” is a subjective human concept, and “disorder” cannot always be obtained from entropy
  • Toward Improved Understanding of the Physical Meaning of Entropy in . . .
    The year 2015 marked the 150th anniversary of “entropy” as a concept in classical thermodynamics Despite its central role in the mathematical formulation of the Second Law and most of classical thermodynamics, its physical meaning continues to be elusive and confusing
  • Entropy | Instructions for Authors - MDPI
    Manuscripts for Entropy should be submitted online at susy mdpi com The submitting author, who is generally the corresponding author, is responsible for the manuscript during the submission and peer review process
  • Applications of Entropy in Data Analysis and Machine Learning: A . . . - MDPI
    Precisely, this paper aims to provide an up-to-date overview of the applications of entropy in data analysis and machine learning, where entropy stands here not only for the traditional instances, but also for more recent proposals inspired by them




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