In this chapter we give main definitions and useful facts of the theory of Gibbs measures of
lattice spin systems. In the first section we give general definitions. This chapter also …

The paper concerns the q-state Potts model (ie with spin values in) on a Cayley tree of
degree (ie with k+ 1 edges emanating from each vertex) in an external (possibly random) …

A Bayesian semi-parametric survival regression model with latent partitions is introduced. Its
goal is to predict survival and to cluster survival patients within the context of building …

We introduce a fast method to estimate the complete-data set of k-nearest-neighbors. This is
equivalent to finding an estimate of the k-nearest-neighbor graph of the data. The method …

We have built a Shallow Gibbs Network model as a Random Gibbs Network Forest to reach
the performance of the Multilayer feedforward Neural Network in a few numbers of …

The model called Structured Potts Neural Network is an hierarchical Bayesian model where
we train individual neural nets to specialize on sub-groups (latent clusters components) …

The perfect learning exists. We mean a learning model that can be generalized, and
moreover, that can always fit perfectly the test data, as well as the training data. We have …

We have modified the Potts Model Swendsen-Wang algorithm to insert some clusters
constraints by applying a modified agglomerative clustering approach (Kurita, 1991). We …

The model called Structured Potts Neural Network is an hierarchical Bayesian model where
we train individual neural nets to specialize on sub-groups (latent clusters components) …

Le but de ce projet de recherche est de développer un modèle de régression bayésien non
paramétrique issu de partitions aléatoires dans un contexte d'analyse de survie. Notre …