<p>The initial probability density that a node using action has a fraction of neighbor nodes with action , computed on a two-dimensional lattice for , , , and a completely connected network (from the broadest to the narrowest probability density distribution). [<i>Inset</i>: (black, continuous) and (red, dotted) for .] Time evolution of the probability densities (black) and (red) in a two-dimensional lattice with for (<i>B</i>) , (<i>C</i>) 5 and (<i>D</i>) 10. For all panels, the dashed line indicates the threshold ; parameter values: system size is , , and .</p
A commonly used characteristic of statistical dependence of adjacency relations in real networks, th...
<p>Fraction of realizations in which the innovation has been adopted <i>P</i>(<i>acceptance</i>) ver...
The study of complex networks, and in particular of social networks, has mostly concentrated on rela...
<p>(A) Network architecture with 21×6 inputs and 7×3 network neurons. The green, red and blue neuron...
International audienceThis article is about multi-agent collective learning in networks. An agent re...
Abstract. Information diffusion over a social network is analyzed by model-ing the successive intera...
2018-11-12Complex systems can be represented as networks of interacting entities or nodes. In numero...
<p>(a) The degree distribution specifies how likely it is for a person to have a particular number o...
We consider the structure learning problem of influence diffusion on social networks from the observ...
Anticoordination and chimera states occur in a two-layer model of learning and coordination dynamics...
We study the dynamics of on-line learning with time-correlated patterns. In this, we make a distinct...
Abstract. We present a deterministic model for on-line social networks (OSNs) based on transitivity ...
<p>Fraction of realizations in which the innovative method has been adopted versus the initial perfo...
<p>Distributions are calculated by aggregating sub-distributions across temporal window. Differences...
In this paper, we study diffusion social learning over weakly connected graphs. We show that the asy...
A commonly used characteristic of statistical dependence of adjacency relations in real networks, th...
<p>Fraction of realizations in which the innovation has been adopted <i>P</i>(<i>acceptance</i>) ver...
The study of complex networks, and in particular of social networks, has mostly concentrated on rela...
<p>(A) Network architecture with 21×6 inputs and 7×3 network neurons. The green, red and blue neuron...
International audienceThis article is about multi-agent collective learning in networks. An agent re...
Abstract. Information diffusion over a social network is analyzed by model-ing the successive intera...
2018-11-12Complex systems can be represented as networks of interacting entities or nodes. In numero...
<p>(a) The degree distribution specifies how likely it is for a person to have a particular number o...
We consider the structure learning problem of influence diffusion on social networks from the observ...
Anticoordination and chimera states occur in a two-layer model of learning and coordination dynamics...
We study the dynamics of on-line learning with time-correlated patterns. In this, we make a distinct...
Abstract. We present a deterministic model for on-line social networks (OSNs) based on transitivity ...
<p>Fraction of realizations in which the innovative method has been adopted versus the initial perfo...
<p>Distributions are calculated by aggregating sub-distributions across temporal window. Differences...
In this paper, we study diffusion social learning over weakly connected graphs. We show that the asy...
A commonly used characteristic of statistical dependence of adjacency relations in real networks, th...
<p>Fraction of realizations in which the innovation has been adopted <i>P</i>(<i>acceptance</i>) ver...
The study of complex networks, and in particular of social networks, has mostly concentrated on rela...