Bayesian methods have become increasingly popular in statistics and machine learning communities for dealing with complex problems. Because these methods are praised by practitioners, it is crucial to have a better understanding of their theoretical properties. This workshop aims at bringing together researchers working on all the aspects of Bayes modeling for complex models from risks bounds, posterior contraction, and properties of the MCMC methods used to conduct the inference.

Invited speakers :

• Arnak Dalalyan
• Alain Durmus
• Peter Grunwald
• Stéphanie van der Pas
  
• James Ridgway
• Elodie Vernet

Registration for the workshop is free but compulsory. Please follow this link to register

•   9:30 - 10:30 – Alain Durmus
• 10:30 - 10:45 – Coffee Break
• 10:45 - 11:45 – Stéphanie van der Pas
• 11:45 - 12:45 – Arnak Dalalyan
• 12:45 - 14:00 – Lunch Break
• 14:00 - 15:00 – Elodie Vernet
• 15:00 - 15:15 – Coffee Break
• 15:15 - 16:15 – James Ridgway
• 16:15 - 17:15 – Peter Grünwald

Jean-Bernard Salomond (UPEC), Ismael Castillo (UPMC), Pierre Alquier (CREST-ENSAE)