2024 Statistics Days in Bordeaux

Welcoming participants

Opening of the JDS 2024

MJLD session:

Group sessions and contributed sessions:

• Young statisticians group session
• Environment and statistics
• Optimal transport
• Statistics applied to medicine
• Bayesian statistics
• Neural networks

Lunch

Semi-plenary guest sessions: 

• "Topological Data Analysis: extracting insights from the “shape” of data " - Kathryn Hess Bellwald, Brain and Mind Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne 
• "On the simulation of extreme events with neural networks" - Stéphane GIRARD, Modèles statistiques bayésiens et des valeurs extrêmes pour données structurées et de grande dimension 

Contributed sessions:

• AEF risks
• Learning from unbalanced data
• Counting data
• Statistics and sport
• Dimension reduction
• Importance sampling

Group sessions and contributed sessions:

• MALIA
• Analysis of topological and geometric data
• Mixed models
• High dimensionality and parsimony
• Processes
• Actuarial Awards

Welcoming cocktail

Semi-plenary invited sessions:

• "Non-parametric estimation of the intensity of a spatial point process using random forests" - Frédéric Lavancier, Centre de Recherche en Économie et Statistique
• "Gene networks: inference, evaluation, use and beyond" - Nathalie Vialaneix, Toulouse Applied Mathematics and Computer Science Unit

Group sessions and contributed sessions:

• Statistics and sport
• Environment and statistics
• Spatial statistics
• Classification
• Omic data
• Markov chains and processes

Contributed sessions :

• Copies
• Longitudinal data
• Directional data
• Piecewise deterministic Markov processes
• Statistics applied to management
• E-learning

"Lucien Le Cam" conference by Cun-Hui Zhang (Rutgers University, Department of Statistics and Biostatistics)

Group sessions and contributed sessions :

• SFB
• ENBIS and Reliability and Uncertainty Group
• Functional data
• Missing data
• Model selection
• Unsupervised classification and mixture model

SFdS General Meeting

Semi-plenary guest sessions:

• "Some statistical reflections on machine learning inspired by physics" - Claire Boyer, Sorbonne University, Institut Universitaire de France 
• "Statistical needs for Exposome Analytics: an Illustrative overview" - Marc Chadeau-Hyam, School of Public Health, Dept of Epidemiology and Biostatistics, Imperial College, London

Group sessions and contributed sessions :

• Extremes and risks
• Conformal prediction
• Statistics and sport
• Survival data, censored data
• Functional data
• Graphs and networks

Semi-plenary invited sessions :

• "Curvature measures for random excursion sets: theoretical and computational developments" - Elena Di Bernardino, Jean Alexandre Dieudonné Laboratory
• "Statistics for qualitative trajectories: applications in sensory data analysis" - Hervé Cardot, University of Burgundy

Social activities

Gala dinner

Invited semi-plenary sessions :

• "Generative models for estimating a posteriori laws: applications to inverse problems and SBI (Simulation-Based Inference) methods" - Sylvain Le Corff, Probability, Statistics and Modelling Laboratory
• "Survival analysis of breast cancer screening programmes" - Maja Pohar-Perme, Institute of Biostatistics and Medical Informatics, Medical faculty, University of Ljubljana 

Group sessions and contributed sessions :

• Teaching statistics
• "Tips and tricks for mathematical statistics
• Statistics applied to medicine
• Robust statistics and anomaly detection
• Regression
• Generative AI

Contributed sessions :

• Statistics and sport
• Mathematical statistics
• Time series
• Composition and distribution data
• SFdS Ensai Prize
• Surveys and polls
• Neural networks

Semi-plenary invited sessions :

• "DPPs everywhere: repulsive point processes for Monte Carlo integration and machine learning" - Rémi Bardenet, CNRS, Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL)
• "Statistical learning in climate sciences: the example of internal gravity waves" - Aurélie Fischer, Probability, Statistics and Modelling Laboratory 

Group sessions and contributed sessions :

• Bayesian statistics
• Causal inference
• Multi-omics
• Statistics applied to industry
• Time series
• Non-parametric density estimation

Closing of the conference