For more than 30 years the MaxEnt workshops have explored the use of Bayesian and Maximum Entropy methods in scientific and engineering applications. All aspects of probabilistic inference, such as foundations, techniques, links with physics and applications in sciences and engineering as well as in social and life science, are of interest.

34th International Workshop on

Bayesian Inference and Maximum Entropy

Methods in Science and Engineering

21-26 september 2014, Château Clos Lucé, Parc Leonardo Da Vinci, Amboise, France

The workshop includes a one-day tutorial session, state-of-the-art invited lectures and contributed papers and poster presentations. All accepted papers will be published in a conference series book by American Institut of physics. Selected papers by the program committee may be edited and published in a book or in special issue of a journal.

 


Important dates

  • 16th of May 2014 : Abstract submission & pre-registration
  • 15th of June 2014 : Selection of paper and Registration
  • September 1, Registration due
  • 15th of September Final paper submission
  • 15th of October paper for publication in AIP conference Proceedings

Tutorials

  1. Modern Probability Theory, Kevin H. Knuth

  2. The Basics of Information Geometry, Ariel Caticha

  3. Voronoi diagrams in information geometry, Franck Nielsen

  4. Foundations and Geometry, John Skilling

  5. Uncertainty quantification for computer model, Udo V. Toussaint

  6. Geometric Structures Induced From Divergence Functions, Jun Zhang

  7. Koszul Information Geometry and Souriau Lie Group Thermodynamics, Frédéric Barbaresco

  8. Bayesian and Information Geometry in signal processing, Ali Mohammad-Djafari


A propos

For more than 30 years the MaxEnt workshops have explored the use of Bayesian and Maximum Entropy methods in scientific and engineering applications. All aspects of probabilistic inference, such as foundations, techniques, links with physics and applications in sciences and engineering as well as in social and life science, are of interest.

34th International Workshop on

Bayesian Inference and Maximum Entropy

Methods in Science and Engineering

21-26 september 2014, Château Clos Lucé, Parc Leonardo Da Vinci, Amboise, France

The workshop includes a one-day tutorial session, state-of-the-art invited lectures and contributed papers and poster presentations. All accepted papers will be published in a conference series book by American Institut of physics. Selected papers by the program committee may be edited and published in a book or in special issue of a journal.

 


Important dates

  • 16th of May 2014 : Abstract submission & pre-registration
  • 15th of June 2014 : Selection of paper and Registration
  • September 1, Registration due
  • 15th of September Final paper submission
  • 15th of October paper for publication in AIP conference Proceedings

Tutorials

  1. Modern Probability Theory, Kevin H. Knuth

  2. The Basics of Information Geometry, Ariel Caticha

  3. Voronoi diagrams in information geometry, Franck Nielsen

  4. Foundations and Geometry, John Skilling

  5. Uncertainty quantification for computer model, Udo V. Toussaint

  6. Geometric Structures Induced From Divergence Functions, Jun Zhang

  7. Koszul Information Geometry and Souriau Lie Group Thermodynamics, Frédéric Barbaresco

  8. Bayesian and Information Geometry in signal processing, Ali Mohammad-Djafari


Sponsors et organisateurs

Documents

XLS

Poster session 2 (Jean-François Bercher, Valérie Girardin, Marcel Reginatto)

Robust Burg Estimation of stationary autoregressive mixtures covariance
Non Parametric Denoising Methods Based on Wavelets : Application to Electron Microscopy Images in Low Time Exposure
Most Likely Maximum Entropy for Population Analysis: a case study in decompression sickness prevention
Comparing Entropy and Energy Goodness-of-fit test for Lévy Distribution
Variational Bayesian Approach with a heavy-tailed prior distribution for solving a non-linear inverse scattering problem
Assessment of two MCMC algorithms convergence for Bayesian estimation of the particle size distribution from multiangle dynamic light scattering
TFBS Prediction with Stochastic Differential Equation and Time Series
Entropy-based goodness-of-fit test for positive stable distribution
On coarse graining of information and its application to pattern recognition
Opening session (Ali Mohammad-Djafari, Frédéric Barbaresco)
Oral session 1 Statistical Manifolds (Jean-François Bercher, Ariel Caticha, Steeve Zozor)
Oral session 2 Entropy Foundation (Ali Mohammad-Djafari, John Skilling)
Oral session 3 Information geometry (Ariel Caticha, Steeve Zozor, Frank Nielsen)
Oral session 4 History of Science (John Skilling, AntonyGarrette)
Oral session 5 Bayesian inference (Frank Nielsen, John Skilling, Romke Brontekoe)
Oral session 6 Foundations and Geometry (John Skilling, Frank Nielsen, Ariel Caticha)

Auteurs

Comparing Entropy and Energy Goodness-of-fit test for Lévy Distribution
Entropy-based goodness-of-fit test for positive stable distribution
Most Likely Maximum Entropy for Population Analysis: a case study in decompression sickness prevention
Non Parametric Denoising Methods Based on Wavelets : Application to Electron Microscopy Images in Low Time Exposure
Non-Negative Matrix Factorization and Term Structure of Interest Rates
On coarse graining of information and its application to pattern recognition
Robust Burg Estimation of stationary autoregressive mixtures covariance
TFBS Prediction with Stochastic Differential Equation and Time Series
Variational Bayesian Approach with a heavy-tailed prior distribution for solving a non-linear inverse scattering problem
Beyond Landau--Pollak and entropic inequalities: geometric bounds imposed on uncertainties sum
The MaxEnt extension of a quantum Gibbs family, convex geometry and geodesics

Nouvelles

SEE will initiate soon preparation of GSI’15 « Geometric Science of Information » conference. Waiting for SEE GSI’15 conference, SEE invite you to submit a paper for SEE MaxEnt’14 “"Maximum Entropy and Bayesian methods in Science and Engineering" conference

that will take place on 21-26 September 2014: https://www.see.asso.fr/maxent14 at Château du Clos Lucé (Last residence of Leonardo Da Vinci), Amboise, France: http://www.vinci-closluce.com/en/

Amboise is at the heart of Loire Valley Castles (http://loire-valley.us/), labeled by UNESCO as World heritage. Le Clos Lucé is at proximity of King Francis the First Amboise Castle (http://loire-valley.us/19-Chateaux/Royal-Chateau-Of-Amboise.html), apex of the French Renaissance and of Vouvray wines vineyards and cellars. Connection from Paris to Amboise by train is only 1h40.

MaxEnt is sponsored by Non-Profit “Jaynes Foundation”. This year, MaxEnt will enlarge its scope with a dedicated focus on “Geometric Science of Information” and “Information Geometry”.

The workshop includes a one day tutorial session, state of the art lectures, invited papers, contributed papers, and poster presentations. Selected papers will be peer reviewed and published in American Institute of Physics (AIP) Proceedings series (http://www.aip.org/). 

MaxEnt workshop is a one week, one track presentations and a very nice place for reflection, exchange and interaction between Mathematics, Physics, Engineering and different applications.

bstracts (one page of about 400 words) of the proposed papers should be received by May 16, 2014.

Would you find attached first Call for Papers and announcement Flyer. More information on MaxEnt’14 webiste http://www.see.asso.fr/maxent14

For your information:

Best regards

F. Barbaresco & A. Mohammad-Djafari

MaxEnt’14 Conference Chairs

Les 630 pages des actes de la conférence SEE MaxEnt’14 « Bayesian Inference and Maximum Entropy Methods in Science and Engineering » ont été édités par AIP « American Institute of Physics ».

proceedings-aip-extrait.pdf

Lieu

Château du Clos Lucé, Amboise (France)

Parc Leonardo Da Vinci

2 Rue du Clos Lucé
37400 Amboise, France
+33 2 47 57 00 73