A metric on the space of probability measures on the state of a large network is introduced, with respect to which the stationary measure of a Markov process on the network is proved under suitable hypotheses to vary uniformly smoothly with parameters and the rate of relaxation to equilibrium to never suddenly decrease
A large deviations principle is established for the joint law of the empirical measure and the flow ...
A large deviations principle is established for the joint law of the empirical measure and the flow ...
We consider the asymptotics of the invariant measure for the process of spatial distribution of N co...
Many notions of network centrality can be formulated in terms of invariant probability vectors of su...
We consider finite-state Markov chains driven by stationary ergodic invertible processes representin...
We address the problem of community detection in networks by introducing a general definition of Mar...
This thesis presents a robust design approach for communication networks that includes capacitation ...
We address the problem of community detection in networks by introducing a general definition of Mar...
We address the problem of community detection in networks by introducing a general definition of Mar...
We address the problem of community detection in networks by introducing a general definition of Mar...
We address the problem of community detection in networks by introducing a general definition of Mar...
This thesis presents a robust design approach for communication networks that includes capacitation ...
We delve into a couple of topics in the theory of Markov chains and stochastic networks. The propert...
The main question posed in this thesis is the characterization of the stability region of a random n...
The main question posed in this thesis is the characterization of the stability region of a random n...
A large deviations principle is established for the joint law of the empirical measure and the flow ...
A large deviations principle is established for the joint law of the empirical measure and the flow ...
We consider the asymptotics of the invariant measure for the process of spatial distribution of N co...
Many notions of network centrality can be formulated in terms of invariant probability vectors of su...
We consider finite-state Markov chains driven by stationary ergodic invertible processes representin...
We address the problem of community detection in networks by introducing a general definition of Mar...
This thesis presents a robust design approach for communication networks that includes capacitation ...
We address the problem of community detection in networks by introducing a general definition of Mar...
We address the problem of community detection in networks by introducing a general definition of Mar...
We address the problem of community detection in networks by introducing a general definition of Mar...
We address the problem of community detection in networks by introducing a general definition of Mar...
This thesis presents a robust design approach for communication networks that includes capacitation ...
We delve into a couple of topics in the theory of Markov chains and stochastic networks. The propert...
The main question posed in this thesis is the characterization of the stability region of a random n...
The main question posed in this thesis is the characterization of the stability region of a random n...
A large deviations principle is established for the joint law of the empirical measure and the flow ...
A large deviations principle is established for the joint law of the empirical measure and the flow ...
We consider the asymptotics of the invariant measure for the process of spatial distribution of N co...