Tag: Bayesian inference

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📅 Entropy 2018: From Physics to Information Sciences and Geometry

RSVPed Might be attending Entropy 2018: From Physics to Information Sciences and Geometry
14-16 May 2018; Auditorium Enric Casassas, Faculty of Chemistry, University of Barcelona, Barcelona, Spain

One of the most frequently used scientific words, is the word “Entropy”. The reason is that it is related to two main scientific domains: physics and information theory. Its origin goes back to the start of physics (thermodynamics), but since Shannon, it has become related to information theory. This conference is an opportunity to bring researchers of these two communities together and create a synergy. The main topics and sessions of the conference cover:

  • Physics: classical Thermodynamics and Quantum
  • Statistical physics and Bayesian computation
  • Geometrical science of information, topology and metrics
  • Maximum entropy principle and inference
  • Kullback and Bayes or information theory and Bayesian inference
  • Entropy in action (applications)

The inter-disciplinary nature of contributions from both theoretical and applied perspectives are very welcome, including papers addressing conceptual and methodological developments, as well as new applications of entropy and information theory.

All accepted papers will be published in the proceedings of the conference. A selection of invited and contributed talks presented during the conference will be invited to submit an extended version of their paper for a special issue of the open access Journal Entropy. 

Entropy 2018 Conference

Entropy | Special Issue: Maximum Entropy and Bayesian Methods

Bookmarked Entropy | Special Issue : Maximum Entropy and Bayesian Methods (mdpi.com)
Open for submission now
Deadline for manuscript submissions: 31 August 2017

A special issue of Entropy (ISSN 1099-4300).

Deadline for manuscript submissions: 31 August 2017

Special Issue Editor


Guest Editor
Dr. Brendon J. Brewer

 

Department of Statistics, The University of Auckland, Private Bag 92019, Auckland 1142, New Zealand
Website | E-MailPhone: +64275001336
Interests: bayesian inference, markov chain monte carlo, nested sampling, MaxEnt

Special Issue Information

Dear Colleagues,

Whereas Bayesian inference has now achieved mainstream acceptance and is widely used throughout the sciences, associated ideas such as the principle of maximum entropy (implicit in the work of Gibbs, and developed further by Ed Jaynes and others) have not. There are strong arguments that the principle (and variations, such as maximum relative entropy) is of fundamental importance, but the literature also contains many misguided attempts at applying it, leading to much confusion.

This Special Issue will focus on Bayesian inference and MaxEnt. Some open questions that spring to mind are: Which proposed ways of using entropy (and its maximisation) in inference are legitimate, which are not, and why? Where can we obtain constraints on probability assignments, the input needed by the MaxEnt procedure?

More generally, papers exploring any interesting connections between probabilistic inference and information theory will be considered. Papers presenting high quality applications, or discussing computational methods in these areas, are also welcome.

Dr. Brendon J. Brewer
Guest Editor

Submission

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed Open Access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1500 CHF (Swiss Francs).

No papers have been published in this special issue yet.