MaxEnt 2007


MaxEnt 2007
is sponsored by


Edwin T. Jaynes International Center



Contact

Dr. Kevin H. Knuth
Department of Physics
University at Albany
Albany NY 12222
USA

Phone: +1-518-442-4653
FAX: +1-518-442-5260
Email: maxent2007@gmail.com

 

MaxEnt 2007

27th International Workshop on
Bayesian Inference and Maximum Entropy Methods in Science and Engineering

The Saratoga Hotel
Saratoga Springs, New York, USA

July 8-13, 2007

IMPORTANT DATES
Detailed Program IS ONLINE NEW
Currently Late Registration

Papers Due: July 6, 2007

TO DO
LOG IN TO YOUR MAXENT ACCOUNT HERE

REGISTER FOR THE CONFERENCE HERE

HOTEL RESERVATIONS HERE
Please do not delay in obtaining your hotel reservation.
This is a popular tourist area and hotels will fill up.

PAPER SUBMISSION
Papers Due: July 6, 2007

Confirmed Invited Speakers  
Prof. Shun-ichi Amari RIKEN, Japan
Dr. Tony Bell UC Berkeley, USA
Prof. Jose M. Bernardo Universitat de Valencia, Spain
Dr. Philip Goyal Cambridge University, United Kingdom
Prof. Phil Gregory University of British Columbia, Canada
Prof. Stephen Roberts University of Oxford, United Kingdom

50 Years of Maximum Entropy and Inference in Physics
This workshop will highlight the 50 th anniversary of Ed Jaynes’ 1957 paper
“Information Theory and Statistical Mechanics” published in The Physical Review. This work introduces the Maximum Entropy Principle, which casts statistical mechanics as a theory of inference rather than a physical theory. Fifty years after this important work, we find ourselves at these workshops applying these concepts to a wide array of problems ranging from astronomy to economics; from medical imaging to quantum mechanics. However, this paradigm shift of looking at a physical theory as a theory of inference is not yet fully appreciated by the physics community. In addition, the knowledge about statistical inference, which has been gained in over 100 years of statistical mechanics, is not yet fully available to the statistics community at large.

Scope
For over 25 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 Techniques, Applications, and Foundations, are of interest. With the rapid growth of computing power, computational techniques such as Markov chain Monte Carlo sampling are of great interest, as are approximate inferential methods. Application areas include, but are not limited to: Astronomy and Astrophysics, Genetics, Geophysics, Medical Imaging, Material Science, Nanoscience, Source Separation, Particle Physics, Quantum Mechanics, Plasma Physics, Chemistry, Earth Science, Climate Studies, Engineering and Robotics. Foundational issues involving probability theory and information theory, and inference and inquiry are also of keen interest as there are yet many open questions.

 

Local Organizers  
Kevin H. Knuth University at Albany (SUNY)
Ariel Caticha University at Albany (SUNY)
Julian Center Creative Research Corp.
Deniz Genšaga University at Albany (SUNY)
Adom Giffin University at Albany (SUNY)
Nabin K. Malakar University at Albany (SUNY)
Carlos Rodriguez University at Albany (SUNY)
Ning Xiang Rensselaer Polytechnic Institute

Advisory Committee
G. L. Bretthorst Washington Univ., USA
A. Caticha University at Albany (SUNY), USA
Julian Center Creative Research Corp.
V. Dose IPP, Germany
G. Erickson Boise State Univ., USA
R. Fischer IPP, Germany
P. M.Goggans University of Mississippi, USA
K. Hanson LANL, USA
K. H. Knuth University at Albany (SUNY), USA
T. Loredo Cornell Univ., USA
A. Mohammad-Djafari LSS-CNRS, France
C. Rodriguez University at Albany (SUNY), USA
J. Skilling Cambridge, UK
C. Ray Smith Univ. of Mississippi, USA
Udo von Toussaint IPP, Germany