Bayesian inference and maximum entropy methods in science and engineering

Organisers: Axel Gandy (Imperial College London, UK); Grigorios Pavliotis (Imperial College London, UK)

Date: 2 – 6 July 2018

Day 1: 10:00 – 20:00
Day 2: 9:00 – 19:00
Day 3: 9:00 – 21:00
Day 4: 9:00 – 18:40
Day 5: 9:00 – 13:00

Venue: The Alan Turing Institute

Further details can be found on the main event website

For over 37 years, the Max Ent workshops have explored the use of Bayesian and Maximum Entropy methods in scientific and engineering applications. The workshop invites contributions on all aspects of probabilistic inference, including novel techniques and applications, and work that sheds new light on the foundations of inference. In previous workshops, areas of application have included astronomy and astrophysics, chemistry, communications theory, cosmology, climate studies, earth science, fluid mechanics, genetics, geophysics, machine learning, material science, medical imaging, nanoscience, source separation, thermodynamics (equilibrium and non-equilibrium), particle physics, plasma physics, quantum mechanics, robotics and social sciences. Bayesian computational techniques such as Markov chain Monte Carlo sampling have been regular topics, as are approximate inferential methods. Foundational issues involving probability theory and information theory, and the novel application of inference to illuminate the foundations of physical theories, have also been of keen interest.


Foundations of MaxEnt
Kevin Knuth (University at Albany, USA)

Parallel computing
Wesley Henderson (University of Mississippi, USA)

Introduction to Bayesian inverse problems
Aretha Teckentrup (University of Edinburgh, UK)

Mean Field Games
Dante Kalise (Imperial College London, UK)

MaxEnt methods for Fokker-Planck equations
Greg Pavliotis (Imperial College London, UK)


Invited speakers:

Urban modelling and MaxEnt principles
Sir Alan Wilson (The Alan Turing Institute, UK)

Foundations of MaxEnt
John Skilling (Maximum Entropy Data Consultants Ltd, UK)

Probabilistic numerical methods
Chris Oates (Newcastle University, UK)

Bayesian global optimization based on surrogate models
Udo von Toussaint (Max-Planck-Institut fuer Plasmaphysik, Germany)

Maximum entropy analysis of flow systems and flow networks
Robert Niven (University of New South Wales, UK)

Bayesian inverse problems
Tony Kennedy (University of Edinburgh, UK)

Hamiltonian Monte Carlo on symmetric spaces
Masoumeh Dashti (University of Sussex, UK)