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Foundations and Modeling of Dynamic Networks Using Dynamic Graph Neural Networks: A Survey [PDF]
IEEE Access, 2020 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
semanticscholar +5 more sources
A Method Based on Temporal Embedding for the Pairwise Alignment of Dynamic Networks [PDF]
Entropy, 2023 In network analysis, real-world systems may be represented via graph models, where nodes and edges represent the set of biological objects (e.g., genes, proteins, molecules) and their interactions, respectively.
Pietro Cinaglia, Mario Cannataro
doaj +2 more sources
Alignment of dynamic networks [PDF]
Bioinformatics, 2017 Motivation: Network alignment (NA) aims to find a node mapping that conserves similar regions between compared networks. NA is applicable to many fields, including computational biology, where NA can guide the transfer of biological knowledge from well ...
V. Vijayan +2 more
semanticscholar +6 more sources
Consecutive feedback-driven constitutional dynamic networks. [PDF]
Proc Natl Acad Sci U S A, 2019 Significance Inspired by nature, where dynamic networks lead to adaptive compositions and emerging functions of the systems, we introduce nucleic-acid–based constitutional dynamic assemblies mimicking natural networks.
Yue L +6 more
europepmc +2 more sources
Dynamic Network Plaid: A Tool for the Analysis of Dynamic Networks [PDF]
Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 2019 Network data that changes over time can be very useful for studying a wide range of important phenomena, from how social network connections change to epidemiology.
Alexandra Lee +2 more
semanticscholar +4 more sources
Deep Learning for Link Prediction in Dynamic Networks Using Weak Estimators
IEEE Access, 2018 Link prediction is the task of evaluating the probability that an edge exists in a network, and it has useful applications in many domains. Traditional approaches rely on measuring the similarity between two nodes in a static context. Recent research has
Carter Chiu, Justin Zhan
doaj +2 more sources
Strategy evolution on dynamic networks [PDF]
Nature Computational Science, 2023 Models of strategy evolution on static networks help us understand how population structure can promote the spread of traits like cooperation. One key mechanism is the formation of altruistic spatial clusters, where neighbors of a cooperative individual ...
Qi Su, Alex McAvoy, J. Plotkin
semanticscholar +1 more source
Reliable Community Search in Dynamic Networks [PDF]
Proceedings of the VLDB Endowment, 2022 Searching for local communities is an important research problem that supports advanced data analysis in various complex networks, such as social networks, collaboration networks, cellular networks, etc.
Yifu Tang +5 more
semanticscholar +1 more source
Dynamic Planning Networks [PDF]
2021 International Joint Conference on Neural Networks (IJCNN), 2021 We introduce Dynamic Planning Networks (DPN), a novel architecture for deep reinforcement learning, that combines model-based and model-free aspects for online planning. Our architecture learns to dynamically construct plans using a learned state-transition model by selecting and traversing between simulated states and actions to maximize information ...
Tasfi, Norman, Capretz, Miriam A M
openaire +4 more sources
IEEE Access, 2022 We reveal hidden social media machinery that has allowed misinformation to thrive among mainstream users, but which is missing from current policy discussions.
Nicholas J. Restrepo +5 more
doaj +1 more source