We present a method to estimate block membership of nodes in a random graph generated by a stochastic blockmodel. We use an embedding procedure motivated by the random dot product graph model, a ...

Stochastic block models (SBMs) serve as a fundamental probabilistic framework for generating and analysing network data with inherent community or modular structure. In these models, nodes are ...

In this paper, we address the question of statistical model selection for a class of stochastic models of biological neural nets. Models in this class are systems of interacting chains with memory of ...

The analysis of social networks and graphs has become increasingly crucial as our understanding of complex systems grows. Modern research has focused on robust sampling techniques that help capture ...

This lecture course is devoted to the study of random geometrical objects and structures. Among the most prominent models are random polytopes, random tessellations, particle processes and random ...