The CSIRO Conference on Computational and Data Intensive Science

Environmental modelling and uncertainty: An introduction to LibBi

Workshop summary

The workshop will provide a practical introduction to the LibBi software package for Bayesian state-space modelling, developed by CSIRO within the CSS TCP.

State-space models combine a process model with a data set in a probabilistic way, rigorously treating uncertainties. They have applications in ecology, biology, hydrology, medicine, econometrics and many other areas. They are particularly useful where the quantification of uncertainty is important—in the parameters, state or observation of a model—and where this informs forecasts or risk-based decision making.

The LibBi software provides a language for specifying state-space models, and Bayesian methods for performing inference with them. It runs on desktop machines up to high-performance compute clusters.


The workshop will begin with a seminar introduction to state-space modelling, including a number of applications. We’ll then work through a number of example models and data sets, running code on CSIRO’s Bragg GPU (graphics processing unit) cluster. There will also be an opportunity for participants to get started on their own projects using the software.


A laptop computer with the ability to connect to the CSIRO VPN.

Background information/Pre-reading Attachments

To find out more about LibBi, visit The introductory paper, available here, is recommended, but not essential, prior reading.

Date and time

Tuesday 1st March, 2015.


Room: Clarendon C, level 2.
Melbourne Convention and Exhibition Centre
1 Convention Place, Melbourne, Victoria

Contact information

Dan Pagendam



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The C3DIS 2017 will bring together researchers with computational and data science specialists from CSIRO, publicly funded research organisations and other invited institutions and organisations. This will enable attendees to share their science outcomes and learnings, and build a community of practice around Computational and Data Intensive science.

Free for CSIRO staff and invited participants