Graph theory provides a language for studying the structure of relations, and it is often used
to study interactions over time too. However, it poorly captures the intrinsically temporal and …

Node connectivity plays a central role in temporal network analysis. We provide a broad
study of various concepts of walks in temporal graphs, that is, graphs with fixed vertex sets …

Networks are well-established representations of social systems, and temporal networks are
widely used to study their dynamics. However, going from temporal network data (ie a …

Network embedding techniques are powerful to capture structural regularities in networks
and to identify similarities between their local fabrics. However, conventional network …

Connectivity and reachability on temporal networks, which can describe the spreading of a
disease, the dissemination of information, or the accessibility of a public transport system …

The study of temporal networks is motivated by the simple and important observation that
just as network structure can affect dynamics, so can structure in time. Just as network …

Temporal networks are commonly used to represent dynamical complex systems like social
networks, simultaneous firing of neurons, human mobility or public transportation. Their …

Time-limited states characterize many dynamical processes on networks: disease-infected
individuals recover after some time, people forget news spreading on social networks, or …

Lack of stationarity in most of the hydroclimatic variables is no longer a topic of debate rather
a reality. It may be hypothesized that alternative methodologies are needed to deal with …

The emerging technologies of wearable wireless devices open entirely new ways to record
various aspects of human social interactions in a broad range of settings. Such technologies …