ABC in Montreal

NIPS 2015 Workshop; December 11, 2015
Montreal, Canada

Approximate Bayesian computation (ABC) or likelihood-free (LF) methods have developed mostly beyond the radar of the machine learning community, but are important tools for a large and diverse segment of the scientific community. This is particularly true for systems and population biology, computational neuroscience, computer vision, healthcare sciences, but also many others.
Interaction between the ABC and machine learning community has recently started and contributed to important advances. In general, however, there is still significant room for more intense interaction and collaboration. Our workshop aims at being a place for this to happen.

Invited Speakers

Program

  • Morning I (8.30 - 10)
    • 8.30-8.40: Opening remarks (winner ISBA travel award, Wentao Li)
    • 8.40-9.20: Mark Beaumont ABC and Population Genetics: any lessons for big data?
    • 9.20-10: Brandon Turner Applications of Likelihood-free Bayesian Methods in Cognitive Science
  • coffee break (10.00 - 10.30)
  • Morning II (10.30 - 12)
    • 10.30 - 11.10: David Nott Uses of ABC in prior choice and Bayesian model checking
    • 11.10 - 11.35: Mijung Park  K2-ABC: ABC with Kernel Embeddings
    • 11.35 - 12:00: Kenji Fukumizu Kernel Mean Particle Filter with Intractable Likelihoods
  • Lunch break (noon - 14.30)
  • Afternoon I (14.30 - 16.00)
    • 14.30-15.10: Rob Deardon ABC-based inference for epidemic models with uncertain underlying contact networks
    • 15.10-15.50: Oksana Chkrebtii Approximate Bayesian Computation for Inference on the Introduction and Spread Patterns of Invasive Species
  • coffee break (16.00 - 16.30)
  • Afternoon II (16.30 - 18.30)
    • 16.30-17: Wentao Li  On the Asymptotic Behavior of ABC
    • 17-17.40: Iain Murray ABC as Learning

Invited talks are in blue, contributed talks in yellow.

Room 511a, Palais des Congrès de Montréal

Organizers

  • Ted Meeds, University of Amsterdam and Vrije University Amsterdam
  • Michael Gutmann, University of Helsinki and Aalto University
  • Dennis Prangle, Reading University
  • Richard Everitt, Reading University
  • Jean-Michel Marin, University of Montpellier

Support

We thank support from The Finnish Centre of Excellence in Computational Inference Research (COIN)
This workshop has been endorsed by ISBA.


Call for Papers


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CALL FOR PAPERS

NIPS 2015 Workshop:

ABC in Montreal

December 11th, 2015

Montreal, Canada

https://sites.google.com/site/abcinmontreal

Important Dates:

  Submission Deadline:  October 16, 2015

  Acceptance Notification:  October 30, 2015

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Approximate Bayesian computation (ABC) or likelihood-free (LF) methods have developed mostly beyond the radar of the machine learning community, but are important tools for a large and diverse segment of the scientific community.  This is particularly true for systems and population biology, computational neuroscience, computer vision, healthcare sciences, but also many others.


Interaction between the ABC and machine learning community has recently started and contributed to important advances. In general, however, there is still significant room for more intense interaction and collaboration. Our workshop aims at being a place for this to happen.


The workshop will consist of invited and contributed talks, poster spotlights, and a poster session.  Rather than a panel discussion we will encourage open discussion between the speakers and the audience.

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Invited Speakers:

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Submissions:

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We invite submissions in NIPS 2015 format with a maximum of 4 pages, excluding references.  Anonymity is not required.  Relevant works that have been recently published or presented elsewhere are allowed, provided that previous publications are explicitly acknowledged.  Authors of accepted papers will be invited to present either a poster or a short talk.  Please submit papers in PDF format abcinmontreal@gmail.com

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Workshop Organizers:

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  • Ted Meeds, University of Amsterdam and Vrije University Amsterdam

  • Michael Gutmann, University of Helsinki and Aalto University

  • Dennis Prangle, Newcastle University

  • Richard Everitt, Reading University

  • Jean-Michel Marin, University of Montpellier


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Acknowledgements:

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ABC in Montreal has been endorsed by ISBA and received support from The Finnish Centre of Excellence in Computational Inference Research (COIN).