The Fifth Workshop on Bayesian Inference for Latent Gaussian Models with Applications
Following four successful meetings in Zürich in 2011, Trondheim 2012 and 2015, and Reykjavik 2013 we are pleased to announce that the Fifth Workshop on Bayesian Inference for Latent Gaussian Models with Applications will be held in Bath 14-16 September 2016. Latent Gaussian models have numerous applications, for example in the social sciences, spatial and spatio-temporal data, epidemiology, climate modelling, and image processing. This workshop brings together researchers who develop methodology and fit datasets in this broad model class.
Location, dates, and activities
Where: University of Bath, Somerset, United KingdomWhen: Wed 14th - Fri 16th September 2016
What: (preliminary timings)
9:00-12:30 Wed 14th, short course on Stan with Michael Betancourt
14:00-17:00 Wed 14th, invited and contributed talks
09:00-16:00 Thu 15th, invited and contributed talks
16:00-later Thu 15th, posters and nibbles
09:00-16:45 Fri 16th, invited and contributed talks
The registration fee is £100.
There is a limited amount of space, so we are asking for expressions of interest. You will be informed of the result and invited to register soon after 1 July, 2016. The registration fee is due 19 August, 2016.
The expression of interest form contains space for abstract submission, and preference will be given to people who submit an abstract for a talk or a poster.
Update 22/7/2016: All of our talk slots have been filled, but any new participants are still welcome to submit a poster abstract up to 19 August, 2016.
Summary of key dates:
Expression of interest is open until the space constraint ceiling is reached
Speakers and participants will be informed and invited to register soon after 1 July, 2016.
Registration fee is due 19 August, 2016.
Conference runs from 14-16 September, 2016.
Short course on Stan
Michael Betancourt will give a 3 hour tutorial on HMC and Stan before lunch on Wednesday 14 September.
This tutorial will aim to provide an interaction introduction to
the use of Stan in R with RStan and ShinyStan. We’ll write
and fit a few models, analyze those fits using numerical and
visual diagnostics, and investigate potential solutions for
Anyone interested in attending is encouraged to download
the latest versions of RStan and ShinyStan before the
conference. For help with installation issues please read
the instructions with careful attention to the RTools
and then consult the Stan Users’ List if there are still problems.
Michael Betancourt, University of Warwick
Samir Bhatt, University of Oxford
Andrew Parnell, University College Dublin
Gavin Shaddick, University of Bath
Theresa Smith, Lancaster University
Sigrunn Holbek Sørbye, UiT The Arctic University of Norway
Aki Vehtari, Aalto University
James V Zidek, University of British Columbia
Janine Illian, University of St Andrews
Finn Lindgren, University of Bath
Daniel Simpson, University of Bath
Andrea Riebler, NTNU, Trondheim