Section: Partnerships and Cooperations
National Initiatives
GdR GeoSto
Members of Dyogene participate in Research Group GeoSto (Groupement de recherche, GdR 3477) http://gdrgeostoch.math.cnrs.fr/ on Stochastic Geometry led by Pierre Calka [Université de Rouen]. This is a collaboration framework for all French research teams working in the domain of spatial stochastic modeling, both on theory development and in applications.
ANR
ANR GAP
Graphs, Algorithms and Probability  PI: Marc Lelarge; started in Jan 2012  48 months. http://www.di.ens.fr/~lelarge/ANRGAP.html
Over the last few years, several research areas have witnessed important progress through the fruitful collaboration of mathematicians, theoretical physicists and computer scientists. One of them is the cavity method. Originating from the theory of mean field spin glasses, it is key to understanding the structure of Gibbs measures on diluted random graphs, which play a key role in many applications, ranging from statistical inference to optimization, coding and social sciences.
The objective of this project is to develop mathematical tools in order to contribute to a rigorous formalization of the cavity method:

From local to global, the cavity method on diluted graphs. We will study the extent to which the global properties of a random process defined on some graph are determined by the local properties of interactions on this graph. To this end, we will relate the cavity method to the analysis of the complex zeros of the partition function, an approach that also comes from statistical mechanics. This will allow us to apply new techniques to the study of random processes on large diluted graphs and associated random matrices.

Combinatorial optimization, network algorithms, statistical inference and social sciences. Motivated by combinatorial optimization problems, we will attack longstanding open questions in theoretical computer science with the new tools developed in the first project. We expect to design new distributed algorithms for communication networks and new algorithms for inference in graphical models. We will also analyze networks from an economic perspective by studying games on complex networks.
ANR MARMOTE
Markovian Modeling Tools and Environments  coordinator: Alain JeanMarie (Inria Maestro); local coordinator (for partner Inria ParisRocquencourt): A. Bušić; Started: January 2013; Duration: 48 months; partners: Inria ParisRocquencourt (EPI DYOGENE), Inria Sophia Antipolis Méditerranée (EPI MAESTRO), Inria Grenoble RhôneAlpes (EPI MESCAL), Université VersailleseSt Quentin, Telecom SudParis, Université ParisEst Creteil, Université Pierre et Marie Curie.
The aim of the project is to realize a modeling environment dedicated to Markov models. One part will develop the Perfect Simulation techniques, which allow to sample from the stationary distribution of the process. A second one will develop parallelization techniques for Monte Carlo simulation. A third one will develop numerical computation techniques for a wide class of Markov models. All these developments will be integrated into a programming environment allowing the specification of models and their solution strategy. Several applications will be studied in various scientific disciplines: physics, biology, economics, network engineering.