We consider some models of random graphs and directed graphs and investigate their behavior near thresholds for the appearance of certain types of connected components. Firstly, we look at the critical window for the appearance of a giant strongly connected component in binomial random digraphs. We provide bounds on the probability that the largest strongly connected component is very large or very small. Next, we study the configuration model for graphs and show new upper bounds on the size of the largest connected component in the subcritical and barely subcritical regimes. We also show that these bounds are tight in some instances. Finally we look at the configuration model for random digraphs. We investigate the barely sub-critical regi...
We study the largest component of a random (multi)graph on n vertices with a given degree sequence. ...
Building on the methods developed in joint work with Béla Bollobás and Svante Janson, we study the p...
We consider a random digraph Dn.uu, ln \ on vert ices l,..., n, where, lor each vertex r., we ch...
We consider some models of random graphs and directed graphs and investigate their behavior near thr...
International audienceIt is known that random directed graphs undergo a phase transition around the ...
A strongly connected component of a directed graph G is a maximal subgraph H of G such that for each...
We consider a model for random hypergraphs with identifiability, an analogue of connectedness. This ...
Over the last few years a wide array of random graph models have been postulated to understand prope...
ABSTRACT. Over the last few years a wide array of random graph models have been pos-tulated to under...
International audienceIn this contribution, we investigate the giant component problem in random gra...
We consider the near-critical Erdos-Rényi random graph G(n, p) and provide a new probabilistic proof...
We study the 'rank 1 case' of the inhomogeneous random graph model. In the subcritical case we deriv...
AbstractLet G be a given graph (modelling a communication network) which we assume suffers from stat...
Abstract. We study the critical behavior of the random digraph D(n, p) for np = 1+ε, where ε = ε(n) ...
In this thesis, we study a recently proposed model of random graphs that exhibit properties which ar...
We study the largest component of a random (multi)graph on n vertices with a given degree sequence. ...
Building on the methods developed in joint work with Béla Bollobás and Svante Janson, we study the p...
We consider a random digraph Dn.uu, ln \ on vert ices l,..., n, where, lor each vertex r., we ch...
We consider some models of random graphs and directed graphs and investigate their behavior near thr...
International audienceIt is known that random directed graphs undergo a phase transition around the ...
A strongly connected component of a directed graph G is a maximal subgraph H of G such that for each...
We consider a model for random hypergraphs with identifiability, an analogue of connectedness. This ...
Over the last few years a wide array of random graph models have been postulated to understand prope...
ABSTRACT. Over the last few years a wide array of random graph models have been pos-tulated to under...
International audienceIn this contribution, we investigate the giant component problem in random gra...
We consider the near-critical Erdos-Rényi random graph G(n, p) and provide a new probabilistic proof...
We study the 'rank 1 case' of the inhomogeneous random graph model. In the subcritical case we deriv...
AbstractLet G be a given graph (modelling a communication network) which we assume suffers from stat...
Abstract. We study the critical behavior of the random digraph D(n, p) for np = 1+ε, where ε = ε(n) ...
In this thesis, we study a recently proposed model of random graphs that exhibit properties which ar...
We study the largest component of a random (multi)graph on n vertices with a given degree sequence. ...
Building on the methods developed in joint work with Béla Bollobás and Svante Janson, we study the p...
We consider a random digraph Dn.uu, ln \ on vert ices l,..., n, where, lor each vertex r., we ch...