14 January 2019
Entropy: 2018 Best Paper Award Winners Selected
You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.
Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.
Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.
Original Submission Date Received: .
The editorial team would like to congratulate the winners of the 2018 Entropy Best Paper Awards. The winner nominations were made by a selection committee, which was chaired by the Editor-in-Chief and supported by twelve Editorial Board Members. The two top-voted papers, in no particular order, have won the 2018 Entropy Best Paper Award (in no particular order):
Critical Behavior in Physics and Probabilistic Formal Languages
Henry W. Lin and Max Tegmark
Entropy 2017, 19(7), 299; doi:10.3390/e19070299.
Available online: https://www.mdpi.com/1099-4300/19/7/299
Download PDF here.
Multiscale Information Decomposition:
Exact Computation for Multivariate Gaussian Processes
Luca Faes, Daniele Marinazzo, and Sebastiano Stramaglia
Entropy 2017, 19(8), 408; doi:10.3390/e19080408
Available online: https://www.mdpi.com/1099-4300/19/8/408
Download PDF here.
We congratulate the authors and we thank them for having chosen Entropy to publish their work.