Inference and Estimation in Probabilistic Time-Series Models

18 June to 20 June 2008

Isaac Newton Institute for Mathematical Sciences, Cambridge, UK

Organisers: David Barber (UCL London, UK), Silvia Chiappa (MPI Tuebingen, Germany) and Taylan Cemgil (University of Cambridge, UK)

in association with the Newton Institute programme Statistical Theory and Methods for Complex, High-Dimensional Data (7 January to 27 June 2008)

Programme | Participants | Registration | Accommodation and Cost | Paper Submission | Important Dates

Proceedings | Participant Address List | Photograph | Web Seminars

Theme of Workshop:

Time-series analysis throws up interesting problems which remain fundamental to several key and as yet unsolved application areas. For example, Bayesian time-series models typically couple all time-points of the series, resulting in intractable inference in high-dimensional latent spaces and therefore requiring approximation.

The workshop will discuss both theories and applications related to probabilistic approaches to time-series analysis. Viewpoints and experiences from researchers belonging to different communities, including machine learning, statistics and statistical physics, are particularly encouraged. For example, approximate inference in the machine learning community tends to be more focussed on deterministic/variational approaches, whilst the statistics community tends to prefer sampling approaches. Amongst others, discussions related to this topic would be appreciated.

More generally, advances in practical and theoretical issues related to probabilistic approaches to time-series modelling, including for example inference, estimation, prediction, classification, clustering and source separation, are appreciated. Novel application areas and the challenges that they bring are also welcome.

Confirmed Invited Speakers:

  • Prof. Zoubin Ghahramani, University of Cambridge
  • Prof. Simon Godsill, University of Cambridge
  • Prof. Eric Moulines, ENST Paris
  • Prof. Manfred Opper, TU Berlin
  • Dr. Omiros Papaspiliopoulos, Universitat Pompeu Fabra Barcelona
  • Dr. Sumeetpal Singh, University of Cambridge
  • Prof. Chris Williams, University of Edinburgh

Paper Submission:

To contribute to the workshop with a talk or poster presentation, it is required to submit a paper, limited to a maximum of 8 pages, by 11 April 2008. Acceptance will be notified by 28 April 2008.

Workshop Book:

We intend to publish a peer reviewed book that will summarise the major contributions to the workshop. Authors of papers presented at the workshop will be invited to submit a version to be published in the book.

Financial Support:

Some funding is available for participants to partially cover the costs of the workshop.

Additional Sponsor:


Local Information | Newton Institute Map | Statistical Theory and Methods for Complex, High Dimensional Data | Workshops | Newton Institute Home Page