COPA2024: 13th Symposium on Conformal and Probabilistic Prediction with Applications Politecnico di Milano Milan, Italy, September 9-11, 2024

Call for Posters is now open!

The 13th Symposium on Conformal and Probabilistic Prediction with Applications (COPA 2024, https://copa-conference.com/) will be held from September 9th to 11th, 2024, at the Politecnico di Milano, Milan, Italy.

Conformal prediction (CP) is a modern machine and statistical learning method that allows the development of valid predictions under weak probabilistic assumptions. CP can be used to form set predictions, using any underlying point predictor, and for very general target variables, allowing the error levels to be controlled by the user. Therefore, CP has been widely used to develop robust forms of probabilistic prediction methodologies and applied to many practical real-life challenges.

Building on the work on CP, various extensions have been developed. This symposium aims to serve as a forum for the presentation of new and ongoing work and the exchange of ideas between researchers on any aspect of conformal and probabilistic prediction and their applications to applicative problems in any field.

Submission Guidelines for Poster Abstracts and Full papers

The Call for Papers closed on the 15^th of April 2024, the Call for Posters closed on the 17^th of May 2024, and decisions have been sent.

Authors of contributions accepted for oral or poster presentation are invited to submit the "camera ready" version of their work on Easychair by the 30^th of June 2024. 

This also applies to authors of the poster abstracts. The abstracts will be included in a separate chapter of the PMLR proceedings.

Please include in the submission a point by point reply to the reviewers comments, the compiled version of the manuscript as well as the source code.

List of Conference Topics

• Theoretical analysis of conformal prediction, including performance guarantees and optimality results
• Applications of conformal prediction
• Novel conformity measures.
• Distribution-free uncertainty quantification
• Conformal anomaly detection.
• Conformal martingale testing and change-point detection
• Conformal prediction for non-Euclidean data
• Conformal prediction for functional and high dimensional data, Multi-output conformal prediction
• Conformal prediction for temporally or spatially dependent data.
• Conformal decision theory.
• Venn prediction and other methods of multi-probability prediction.
• Distributional prediction and Conformal Predictive Distributions
• Algorithmic information theory.
• Software implementations of conformal prediction frameworks and methods.
• Conformal prediction for Explainability, Causality and Fairness, Accountability and Transparency (FAT).

The Committee is open to considering any other recent and cutting-edge development related to Conformal and Probabilistic Prediction.

For questions about submissions, please email Matteo.Fontana@rhul.ac.uk