- Start: Jun 30, 2019
- End: Jul 5, 2019
- Location: Garching
- Host: IPP
39th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering
Main topics of the workshop are the application of Bayesian inference and the maximum entropy principle to inverse problems in science, machine learning, information theory and engineering.
Inverse and uncertainty quantification (UQ) problems arise from a large variety of applications, such as earth science, astrophysics, material and plasma science, imaging in geophysics and medicine, nondestructive testing, density estimation, remote sensing, Gaussian process (GP) regression, optimal experimental design, data assimilation and data mining.
The workshop thus invites contributions on all aspects of probabilistic inference, including novel techniques and applications, and work that sheds new light on the foundations of inference.
- Abstract submission: 15 March - 30 April
- Notification: 15 May
- Early registration: 01 May - 31 May
- Registration: 01 June - 15 June
- Allen Caldwell (MPI f. Physik, D)
- Ariel Caticha (SUNY Albany, US)
- Faidon-Stelios Koutsourelakis (TUM, D)
- Olivier Le Maître (LIMSI, F)
- Stephen Roberts (Univ. Oxford, UK)
- John Skilling (MEDC, UK)
E.T. Jaynes Foundation
Max-Planck-Institut für Plasmaphysik
Publishing Partner and Sponsor: Journal "entropy"
Entropy (ISSN 1099-4300; IF 2.419) is an open access journal which maintains a rigorous and fast peer-review system with a median publication time of 44 days from submission to publication online. It is fully covered by the leading indexing and abstracting services, including Scopus and SCIE (Web of Science), Google Scholar and MathSciNet. You are very welcomed to visit the journal website for more information.