Results 51 to 60 of about 4,648,552 (299)
Random walk centrality for temporal networks
New Journal of Physics, 2014 Nodes can be ranked according to their relative importance within a network. Ranking algorithms based on random walks are particularly useful because they connect topological and diffusive properties of the network. Previous methods based on random walks,
Luis E C Rocha, Naoki Masuda
doaj +1 more source
Backtracking and Mixing Rate of Diffusion on Uncorrelated Temporal Networks
Entropy, 2017 We consider the problem of diffusion on temporal networks, where the dynamics of each edge is modelled by an independent renewal process. Despite the apparent simplicity of the model, the trajectories of a random walker exhibit non-trivial properties ...
Martin Gueuning +2 more
doaj +1 more source
Foundations and Modeling of Dynamic Networks Using Dynamic Graph Neural Networks: A Survey
IEEE Access, 2021 Dynamic networks are used in a wide range of fields, including social network analysis, recommender systems and epidemiology. Representing complex networks as structures changing over time allow network models to leverage not only structural but also ...
Joakim Skarding +2 more
doaj +1 more source
Effects of memory on spreading processes in non-Markovian temporal networks
New Journal of Physics, 2019 Many biological, social and man-made systems are better described in terms of temporal networks, i.e. networks whose links are only present at certain points in time, rather than by static ones. In particular, it has been found that non-Markovianity is a
Oliver E Williams +2 more
doaj +1 more source
Discovering Association Rules with Graph Patterns in Temporal Networks
Tsinghua Science and Technology, 2023 Discovering regularities between entities in temporal graphs is vital for many real-world applications (e.g., social recommendation, emergency event detection, and cyberattack event detection). This paper proposes temporal graph association rules (TGARs)
Chu Huang +4 more
doaj +1 more source
A Unified Theoretical and Deep Learning Framework for Temporal Link Prediction in Dynamic Networks
IEEE AccessTemporal networks extend complex networks by explicitly incorporating the time dimension into the analysis of entities and their interactions. With the rapid growth of large-scale social and information networks, modeling time-evolving relationships has ...
Jo Cheriyan +2 more
doaj +1 more source
Extending Conditional Simple Temporal Networks with Partially Shrinkable Uncertainty [PDF]
, 2018 The proper handling of temporal constraints is crucial in many domains. As a particular challenge, temporal constraints must be also handled when different specific situations happen (conditional constraints) and when some event occurrences can be only ...
Carlo Combi +3 more
core +1 more source
Modelling temporal networks with scientific machine learning. [PDF]
, 2023 Temporal networks appear in applications ranging from symptom prediction to social networks to epidemiology. This thesis proposes a flexible framework for modelling temporal network progression which utilises a combination of singular value decomposition,
Smith, Connor
core +1 more source
Diversity and complexity in neural organoids
FEBS Letters, EarlyView.Neural organoid research aims to expand genetic diversity on one side and increase tissue complexity on the other. Chimeroids integrate multiple donor genomes within single organoids. Self‐organising multi‐identity organoids, exogenous cell seeding, or enforced assembly of region‐specific organoids contribute to tissue complexity.
Ilaria Chiaradia, Madeline A. Lancaster
wiley +1 more source
Frontiers in PhysicsIntroductionInnovative energy startups are expediting the energy transition through the adoption of emerging technologies, including blockchain, fintech, artificial intelligence, and crowdfunding.
Ying Wang, Qing Guan
doaj +1 more source