John Cherian (Stanford University) Conformal Prediction with Conditional Guarantees Abstract : We consider the problem of constructing distribution-free prediction sets with finite-sample conditional guarantees. Prior work has shown that it is impossible to provide exact conditional coverage universally in finite samples.

Ambroise Carton  (RTBF  - journaliste pour Décrypte, la cellule de datajournalisme et de fact-checking de la RTBF) Enhancing Data Literacy in Journalism – What we learned with the Décrypte Team at RTBF Abstract : Are journalists proficient data analysts?

John Cherian (Stanford University) Election Modeling in 2024: A Conformal Inference Approach Abstract : We consider a high-stakes application of statistical inference: uncertainty quantification for election night modeling.

SEMINAR by Niels Richard Hansen (University of Copenhagen) on "The Local Covariance Measure in Survival Analysis" Abstract : The local covariance measure (LCM) quantifies deviations from conditional local independence (CLI) between two time-continuous stochastic processes. It is a function of time defined as the expectation of a suitably defined stochastic integral.

SEMINAR by Jeffrey Näf (Institut national de recherche en sciences et technologies du numérique, INRIA) on "Imputation under Missing at Random: How to Impute and How to Evaluate Imputations" Abstract : In this workshop we take a deep dive into missing values from the standpoint of imputation.

   ! ! !  CANCELLED  ! ! !   SEMINAR by Thomas Nagler (LMU Munich) on "An new bootstrap for time series" Abstract : Resampling methods such as the bootstrap have proven invaluable in statistics and machine learning.

Léon Kourtis, data scientist, Montpellier will give a presentation on Beyond Numbers: An Introduction to the Role of Data Science inside Teams and Federations This presentation will delve into the current role of data science in practical applications in sports and its future perspectives.

Christophe Ley, University of Luxembourg will give a presentation on Statistically Enhanced Learning for Sports Analytics and Injury Prevention Abstract: In this talk, I will describe how one can use probability distributions to model the outcomes of football matches, and how this can be combined with machine learning procedures to predict big tournaments and hereby even outperform bookmakers.

09:00 – 09:05 : Opening 09:05 - 09:30 : Morine DELHELLE "Copula based dependent censoring in cure models" Abstract : In survival data analysis datasets with both a cure fraction (individuals who will never experience the event of interest) and dependent censoring (loss of follow-up for a reason linked to the event of interest before the occurence of this event) are not scarce and it is important

Christian Hirsch (Aarhus, Denmark) will give a presentation on On the topology of higher-order age-dependent random connection models Abstract: Preferential attachment is a popular mechanism for generating scale-free networks. While it offers a compelling narrative, the underlying reinforced processes make it difficult to rigorously establish subtle properties.