The objective of this autumn school is to provide a comprehensive overview of Bayesian methods for complex settings: modelling techniques, computational advances, theoretical guarantees and practical implementation. It will include two masterclasses, on Sequential Monte Carlo and on Bayesian causal inference, tutorials on NIMBLE and on Bayesian Statistics with Python, and a selection of invited and contributed talks.

Information

The initial deadline for pre-registration has passed. You can still pre-register directly on the CIRM website to be added to the waiting list. As the capacity of CIRM is limited, there is a cap on the number of attendees and we cannot guarantee that all scientists who pre-register will be able to participate. You will be soon informed if your application has been selected, otherwise you will be added to the waiting list and contacted if a slot opens.

There is no registration fee. Room and board are available for all participants, and should be paid directly to CIRM (you will receive information about this step in due course). The organizers have secured funding to cover the room and board costs of a number of participants: if you are interested, please apply when you pre-register. We do not have funding to cover travel expenses.

Sponsors

• Centre International de Rencontres Mathématiques
• Société Française de Statistique
• Université Paris Dauphine - PSL
• INRAE Département MathNUM
• Centre Inria de l’Université Grenoble Alpes
• LabEx PERSYVAL-Lab
• European Research Council - Blackjack
• Laboratoire de probabilités statistique & modélisation
• Essec Business School

Committees

• Scientific committee

  • Florence Forbes
  • Sylvia Frühwirth-Schnatter
  • Olivier Gimenez
  • Eric Parent
  • Igor Pruenster
  • Christian Robert
  • Judith Rousseau
  
  

• Organizing committee

  • Sophie Ancelet
  • Julyan Arbel
  • Rémi Bardenet
  • Anna Bonnet
  • Marie-Pierre Etienne
  • Sarah Filippi
  • Guillaume Kon Kam King
  • Pierre Jacob
  • Robin Ryder