[Statlist] INI Workshop, June 2-6: Calibrating prediction uncertainty -> Call for contributions

[Ziegel Johanna]

Dear All,

I would like to draw your attention to the workshop “Calibrating prediction uncertainty: statistics and machine learning perspectives" to be held at Isaac Newton Institute (INI) in Cambridge, England from June 2nd to 6th, 2025.

We welcome submissions for contributed talks and posters with a deadline for applications on February 2nd, 2025.

For more information, please see https://www.newton.ac.uk/event/rclw02/.

The workshop will focus on methodologies and frameworks for calibrating probabilistic predictions, bringing together the statistical and the machine learning communities. The workshop aims to build new synergies between calibration approaches in statistics and machine learning, with a focus on calibration problems for Gaussian processes, kernel methods, deep learning and generative models. To this end, the workshop aims to clarify the plethora of existing concepts related to calibration of probabilistic predictions as well as to discuss open problems related to multivariate and non-Euclidean outcomes, for which classical concepts of prediction evaluation and calibration require revision and extension.

The workshop will start with four invited introductory lectures:
Sayan Mukherjee (Leipzig University, Max Planck Institute for Mathematics in the Sciences and Duke University): Calibration in machine learning models
Johanna Ziegel (ETH Zurich): Calibration of probabilistic predictions
Vladimir Vovk (Royal Holloway, University of London): Calibrating prediction uncertainty with validity guarantees
Richard Wilkinson (University of Nottingham): Bayesian methods for calibration of computer models

Further invited speakers include:
Sam Allen (Karlsruhe Institute of Technology)
David Bolin (King Abdullah University of Science and Technology)
Philip Dawid (University of Cambridge)
Chris Ferro (University of Exeter)
Katerina Papagiannouli (University of Pisa)

With best wishes,
Johanna Ziegel, on behalf of the workshop organisers
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