MaxEnt2023

42nd International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering.

Scope

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.

Frontiers of Nested Sampling

Meeting-withing-a-meeting: Wednesday, July 5th 2023

Last year's Nature paper "Nested sampling for physical scientists" [1] represents a 'state of the union' for a truly cross-disciplinary community. Nested sampling is a radical computational and mathematical technique for performing a variety of challenging tasks simultaneously: scanning and optimising a priori unknown mathematical functions, generating a compressed representation (samples) and integrating them (partition functions). This Swiss-army knife has applications from particle physics through biochemistry and machine learning to astrophysics and cosmology.

Since it's creation by John Skilling in 2004 [5], over the past two decades it has come of age in a world of greater computing power and algorithmic innovation. There are a host of diverse, robust and effective implementations of Skilling's original algorithm, applied across the spectrum of science, as well as a burgeoning collection of extensions to the theory, with a recent flourishing of combinations of NS with machine learning techniques.

We invite researchers to a meeting across community divides, sharing ideas and innovations across disciplines, discussing the frontier problems and the research directions over the next two decades.

[1] Nested Sampling for Physical Scientists (Nature)
[2] Nested Sampling for Frequentist Computation (PRL)
[3] Nested Sampling for Materials (EPJB)
[4] Nested Sampling for Cosmology (MNRAS)
[5] Nested Sampling for General Bayesian Computation (Bayesian Analysis)

Important Dates

• Abstract submission deadline: 20 March extended to 31 March 2023
• Notification: 01 April 2023
• Early registration deadline: 15 April 2023
• Registration deadline: 15 June 2023