Spreading processes on graphs are a natural model for a wide variety of real-world phenomena, including information or behaviour spread over social networks, biological diseases spreading over contact or trade networks, and the potential flow of goods over logistical infrastructure. Often, the networks over which these processes spread are dynamic in nature, and can be modeled with graphs whose structure is subject to discrete changes over time, i.e. with temporal graphs. Here, we consider temporal graphs in which edges are available at specified timesteps, and study the problem of deleting edges from a given temporal graph in order to reduce the number of vertices (temporally) reachable from a given starting point. This could be used to co...
abstract: This thesis discusses three recent optimization problems that seek to reduce disease sprea...
Software implementation available at https://doi.org/10.5281/zenodo.3369893Time-limited states chara...
Current approaches for modeling propagation in networks (e.g., of diseases, computer viruses, rumors...
Spreading processes on graphs are a natural model for a wide variety of real-world phenomena, inclu...
Spreading processes on graphs are a natural model for a wide variety of real-world phenomena, includ...
In many settings there is a need to reduce the spread of something undesirable, such as a virus, thr...
Temporal graphs abstractly model real-life inherently dynamic networks. Given a graph G, a temporal ...
The static graph-based models of complex networks have enjoyed great success in describing various p...
We present a contact-based model to study the spreading of epidemics by means of extending the dynam...
peer-reviewedWe present a contact-based model to study the spreading of epidemics by means of extend...
A temporal graph is a dynamic graph where every edge is assigned a set of integer time labels that i...
A temporal graph is a dynamic graph where every edge is assigned a set of integer time labels that i...
Computing a (short) path between two vertices is one of the most fundamental primitives in graph alg...
In this work we consider temporal networks, i.e. networks defined by a labeling λ assigning to ea...
We show that the TEMPORAL GRAPH EXPLORATION PROBLEM is NP-complete, even when the underlying graph h...
abstract: This thesis discusses three recent optimization problems that seek to reduce disease sprea...
Software implementation available at https://doi.org/10.5281/zenodo.3369893Time-limited states chara...
Current approaches for modeling propagation in networks (e.g., of diseases, computer viruses, rumors...
Spreading processes on graphs are a natural model for a wide variety of real-world phenomena, inclu...
Spreading processes on graphs are a natural model for a wide variety of real-world phenomena, includ...
In many settings there is a need to reduce the spread of something undesirable, such as a virus, thr...
Temporal graphs abstractly model real-life inherently dynamic networks. Given a graph G, a temporal ...
The static graph-based models of complex networks have enjoyed great success in describing various p...
We present a contact-based model to study the spreading of epidemics by means of extending the dynam...
peer-reviewedWe present a contact-based model to study the spreading of epidemics by means of extend...
A temporal graph is a dynamic graph where every edge is assigned a set of integer time labels that i...
A temporal graph is a dynamic graph where every edge is assigned a set of integer time labels that i...
Computing a (short) path between two vertices is one of the most fundamental primitives in graph alg...
In this work we consider temporal networks, i.e. networks defined by a labeling λ assigning to ea...
We show that the TEMPORAL GRAPH EXPLORATION PROBLEM is NP-complete, even when the underlying graph h...
abstract: This thesis discusses three recent optimization problems that seek to reduce disease sprea...
Software implementation available at https://doi.org/10.5281/zenodo.3369893Time-limited states chara...
Current approaches for modeling propagation in networks (e.g., of diseases, computer viruses, rumors...