In this paper we introduce a general Markov chain model of dynamical processes on networks. In this model, nodes in the network can adopt a finite number of states and transitions can occur that involve multiple nodes changing state at once. The rules that govern transitions only depend on measures related to the state and structure of the network and not on the particular nodes involved. We prove that symmetries of the network can be used to lump equivalent states in state-space. We illustrate how several examples of well-known dynamical processes on networks correspond to particular cases of our general model. This work connects a wide range of models specified in terms of node-based dynamical rules to their exact continuous-time Markov c...
This paper proposes a mathematical framework for modelling the evolution of dynamic networks. Such ...
Automata networks model all finite discrete dynamics. Each automaton has a state, evolving in discre...
This paper proposes a mathematical framework for modelling the evolution of dynamic networks. Such ...
The dynamics of disease transmission strongly depends on the properties of the population contact ne...
We study evolutionary game dynamics on networks (EGN), where players reside in the vertices of a gra...
We study evolutionary game dynamics on networks (EGN), where players reside in the vertices of a gra...
We study evolutionary game dynamics on networks (EGN), where players reside in the vertices of a gra...
In this paper, we outline a model of graph (or network) dynamics based on two ingredients. The first...
Adaptive networks are characterised by mutual dependencies between nodes' local state changes and ev...
We present a stochastic dynamics model of coupled evolution for the binary states of nodes and links...
Recent theoretical work on the modeling of network structure has focused primarily on networks that ...
We derive explicit formulae to quantify the Markov chain state-space compression, or lumping, that c...
This chapter discusses the interplay between structure and dynamics in complex networks. Given a par...
We study binary state dynamics on a network where each node acts in response to the average state of...
2Stochastic processes on complex networks, where each node is in one of several compartments, and ne...
This paper proposes a mathematical framework for modelling the evolution of dynamic networks. Such ...
Automata networks model all finite discrete dynamics. Each automaton has a state, evolving in discre...
This paper proposes a mathematical framework for modelling the evolution of dynamic networks. Such ...
The dynamics of disease transmission strongly depends on the properties of the population contact ne...
We study evolutionary game dynamics on networks (EGN), where players reside in the vertices of a gra...
We study evolutionary game dynamics on networks (EGN), where players reside in the vertices of a gra...
We study evolutionary game dynamics on networks (EGN), where players reside in the vertices of a gra...
In this paper, we outline a model of graph (or network) dynamics based on two ingredients. The first...
Adaptive networks are characterised by mutual dependencies between nodes' local state changes and ev...
We present a stochastic dynamics model of coupled evolution for the binary states of nodes and links...
Recent theoretical work on the modeling of network structure has focused primarily on networks that ...
We derive explicit formulae to quantify the Markov chain state-space compression, or lumping, that c...
This chapter discusses the interplay between structure and dynamics in complex networks. Given a par...
We study binary state dynamics on a network where each node acts in response to the average state of...
2Stochastic processes on complex networks, where each node is in one of several compartments, and ne...
This paper proposes a mathematical framework for modelling the evolution of dynamic networks. Such ...
Automata networks model all finite discrete dynamics. Each automaton has a state, evolving in discre...
This paper proposes a mathematical framework for modelling the evolution of dynamic networks. Such ...