Results 31 to 40 of about 9,577,753 (319)
A Novel Temporal Network-Embedding Algorithm for Link Prediction in Dynamic Networks
Entropy, 2023 Understanding the evolutionary patterns of real-world complex systems such as human interactions, biological interactions, transport networks, and computer networks is important for our daily lives.
Khushnood Abbas +5 more
doaj +1 more source
Detecting the driver nodes of temporal networks
New Journal of Physics, 2023 Detecting the driver nodes of complex networks has garnered significant attention recently to control complex systems to desired behaviors, where nodes represent system components and edges encode their interactions.
Tingting Qin, Gaopeng Duan, Aming Li
doaj +1 more source
A Robust Comparative Analysis of Graph Neural Networks on Dynamic Link Prediction
IEEE Access, 2022 Graph neural networks (GNNs) are rapidly becoming the dominant way to learn on graph-structured data. Link prediction is a near-universal benchmark for new GNN models. Many advanced models such as Dynamic graph neural networks (DGNNs) specifically target
Joakim Skarding +3 more
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Temporal Network Creation Games
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023 Most networks are not static objects, but instead they change over time. This observation has sparked rigorous research on temporal graphs within the last years. In temporal graphs, we have a fixed set of nodes and the connections between them are only available at certain time steps. This gives rise to a plethora of algorithmic problems on such graphs,
Bilo' D. +6 more
openaire +3 more sources
Static-Dynamic Temporal Networks for Parkinson’s Disease Detection and Severity Prediction
IEEE transactions on neural systems and rehabilitation engineering, 2023 Most patients with Parkinson’s disease (PD) have different degrees of movement disorders, and effective gait analysis has a huge potential for uncovering hidden gait patterns to achieve the diagnosis of patients with PD. In this paper, the Static-Dynamic
Chenhui Dong +5 more
semanticscholar +1 more source
Effective Influence Spreading in Temporal Networks With Sequential Seeding
IEEE Access, 2020 The spread of influence in networks is a topic of great importance in many application areas. For instance, one would like to maximise the coverage, limiting the budget for marketing campaign initialisation and use the potential of social influence.
Radosaw Michalski +2 more
doaj +1 more source
Real-Time Video Super-Resolution with Spatio-Temporal Networks and Motion Compensation [PDF]
Computer Vision and Pattern Recognition, 2016 Convolutional neural networks have enabled accurate image super-resolution in real-time. However, recent attempts to benefit from temporal correlations in video super-resolution have been limited to naive or inefficient architectures.
Jose Caballero +6 more
semanticscholar +1 more source
Homogenous mixing and network approximations in discrete-time formulation of a SIRS model
Journal of Biological Dynamics, 2021 A discrete-time deterministic epidemic model is proposed to better understand the contagious dynamics and the behaviour observed in the incidence of real infectious diseases.
Ilaria Renna
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Predicting Critical Nodes in Temporal Networks by Dynamic Graph Convolutional Networks
Applied Sciences, 2023 Many real-world systems can be expressed in temporal networks with nodes playing different roles in structure and function, and edges representing the relationships between nodes.
Enyu Yu +4 more
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Temporal Label Walk for Community Detection and Tracking in Temporal Network
Applied Sciences, 2019 The problem of temporal community detection is discussed in this paper. Main existing methods are either structure-based or incremental analysis. The difficulty of the former is to select a suitable time window.
Zheliang Liu +4 more
doaj +1 more source