This workshop will focus on exploring the latest advancements in Approximate Inference methods, with an emphasis on techniques such as Variational Inference and its related approaches. We aim to explore recent breakthroughs in computer science and statistics that enable inference across large-scale models and big datasets, surpassing conventional simulation-based methods. The workshop will bring together researchers from statistics, computer science, and econometrics to exchange ideas on cutting-edge methodological advances and their practical applications.

Confirmed Speakers:

Daniele Bianchi, Queen Mary University of London

Emilie Chouzenoux, Inria Saclay

Justin Domke, UMass Amherst

Maurizio Filippone, KAUST

Jeremias Knoblauch, University College London

Pierre Latouche, Université Clermont Auvergne, CNRS 

Roberto Leon-Gonzalez, GRIPS, Tokyo

Yingzhen Li, Imperial College London

Judith Rousseau, Université Paris Dauphine