Inference and learning are becoming increasingly important in many areas of science and engineering. Typically stated in the framework of computer science, statistics, or information theory, these problems are also linked to concepts and approaches native to statistical physics. This interdisciplinary field has seen a recent explosion of activity, resulting in new algorithms and new methods of analysis. The aim of this workshop is to enforce research on interface between these fields, with the focus on statistical physics, by presentations of the most recent progress and discussions of future directions. The workshop will include longer invited talks, shorter contributed talks and plenty of time for discussions and skiing in the French Alps.

Specific topics will include:

  • Recent Advances in Statistical Inference and Learning
  • Artificial Neural Networks
  • Applications and Theory of Message Passing Algorithms
  • Applications of Statistical Physics in Inference and Learning
  • Compressed sensing and sparse reconstruction
  • Rigorous Results Confirming and Extending Statistical Physics Conjectures