58 citations · 224 across the 17 of their papers we have counts for
20 papers
Towards inferring network properties from epidemic data
István Z. Kiss, Luc Berthouze, Wasiur R. KhudaBukhsh
Epidemic propagation on networks represents an important departure from traditional massaction models. However, the high-dimensionality of the exact models poses a challenge to bot…
Probabilistic predictions of SIS epidemics on networks based on population-level observations
Tanja Zerenner, Francesco Di Lauro, Masoumeh Dashti +2
We predict the future course of ongoing susceptible-infected-susceptible (SIS) epidemics on regular, Erdős-Rényi and Barabási-Albert networks. It is known that the contact network…
The impact of network properties and mixing on control measures and disease-induced herd immunity in epidemic models: a mean-field model perspective
Francesco Di Lauro, Luc Berthouze, Matthew D. Dorey +2
The contact structure of a population plays an important role in transmission of infection. Many ``structured models'' capture aspects of the contact structure through an underlyin…
PDE-limits of stochastic SIS epidemics on networks
Francesco Di Lauro, Jean-Charles Croix, Luc Berthouze +1
Stochastic epidemic models on networks are inherently high-dimensional and the resulting exact models are intractable numerically even for modest network sizes. Mean-field models p…
A new method for the robust characterisation of pairwise statistical dependency between point processes
Antoine Messager, Nicos Georgiou, Luc Berthouze
The robust detection of statistical dependencies between the components of a complex system is a key step in gaining a network-based understanding of the system. Because of their s…
Mapping structural diversity in networks sharing a given degree distribution and global clustering: Adaptive resolution grid search evolution with Diophantine equation-based mutations
Peter Overbury, István Z. Kiss, Luc Berthouze
Methods that generate networks sharing a given degree distribution and global clustering can induce changes in structural properties other than that controlled for. Diversity in st…
Epidemic threshold in pairwise models for clustered networks: closures and fast correlations
Rosanna C. Barnard, Luc Berthouze, Péter L. Simon +1
The epidemic threshold is probably the most studied quantity in the modelling of epidemics on networks. For a large class of networks and dynamics the epidemic threshold is well st…
Inferring the time-varying functional connectivity of large-scale computer networks from emitted events
Antoine Messager, George Parisis, Istvan Z Kiss +3
We consider the problem of inferring the functional connectivity of a large-scale computer network from sparse time series of events emitted by its nodes. We do so under the follow…
Edge-based compartmental modelling of an SIR epidemic on a dual-layer static-dynamic multiplex network with tunable clustering
Rosanna C Barnard, Istvan Z Kiss, Luc Berthouze +1
The duration, type and structure of connections between individuals in real-world populations play a crucial role in how diseases invade and spread. Here, we incorporate the aforem…
Generation and analysis of networks with a prescribed degree sequence and subgraph family: Higher-order structure matters
Martin Ritchie, Luc Berthouze, Istvan Z Kiss
Designing algorithms that generate networks with a given degree sequence while varying both subgraph composition and distribution of subgraphs around nodes is an important but chal…
Using novelty-biased GA to sample diversity in graphs satisfying constraints
Peter Overbury, Luc Berthouze
The structure of the network underlying many complex systems, whether artificial or natural, plays a significant role in how these systems operate. As a result, much emphasis has b…
Oscillating epidemics in a dynamic network model: stochastic and mean-field analysis
András Szabó-Solticzky, Luc Berthouze, Istvan Z. Kiss +1
An adaptive network model using SIS epidemic propagation with link-type dependent link activation and deletion is considered. Bifurcation analysis of the pairwise ODE approximation…
The impact of constrained rewiring on network structure and node dynamics
P. Rattana, L. Berthouze, I. Z. Kiss
In this paper, we study an adaptive spatial network. We consider an SIS (susceptible-infectedsusceptible) epidemic on the network, with a link/contact rewiring process constrained…
Beyond clustering: Mean-field dynamics on networks with arbitrary subgraph composition
Martin Ritchie, Luc Berthouze, Istvan Z. Kiss
Clustering is the propensity of nodes that share a common neighbour to be connected. It is ubiquitous in many networks but poses many modelling challenges. Clustering typically man…
Markers of criticality in phase synchronisation
Maria Botcharova, Simon F. Farmer, Luc Berthouze
The concept of the brain as a critical system is very attractive because systems close to criticality are thought to maximise their dynamic range of information processing and comm…
Higher-order structure and epidemic dynamics in clustered networks
Martin Ritchie, Luc Berthouze, Thomas House +1
Clustering is typically measured by the ratio of triangles to all triples, open or closed. Generating clustered networks, and how clustering affects dynamics on networks, is reason…
Identification of criticality in neuronal avalanches: II. A theoretical and empirical investigation of the driven case
Caroline Hartley, Timothy J Taylor, Istvan Z Kiss +2
The observation of apparent power-laws in neuronal systems has led to the suggestion that the brain is at, or close to, a critical state and may be a self-organised critical system…
A maximum likelihood based technique for validating detrended fluctuation analysis (ML-DFA)
Maria Botcharova, Simon F Farmer, Luc Berthouze
Detrended Fluctuation Analysis (DFA) is widely used to assess the presence of long-range temporal correlations in time series. Signals with long-range temporal correlations are typ…
Identification of criticality in neuronal avalanches: I. A theoretical investigation of the non-driven case
Timothy J. Taylor, Caroline Hartley, Péter L. Simon +2
In this paper we study a simple model of a purely excitatory neural network that, by construction, operates at a critical point. This model allows us to consider various markers of…
A power-law distribution of phase-locking intervals does not imply critical interaction
Maria Botcharova, Simon F. Farmer, Luc Berthouze
Neural synchronisation plays a critical role in information processing, storage and transmission. Characterising the pattern of synchronisation is therefore of great interest. It h…