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Dynamic Graph Generation Network: Generating Relational Knowledge from Diagrams
[article]
2017
arXiv
pre-print
Preserved Fulltext
Specifically, we propose a dynamic graph-generation network that is based on dynamic memory and graph theory. ...
To tackle this problem, we propose a unified diagram-parsing network for generating knowledge from diagrams based on an object detector and a recurrent neural network designed for a graphical structure ...
In the graph generation branch, we pass local features f (l) from n 2 candidates to the dynamic graph generation network (DGGN) with a global feature f (g) . ...
arXiv:1711.09528v1
fatcat:odt4vse6ozfbjkaq2362hf74e4
Dynamic Graph Generation Network: Generating Relational Knowledge from Diagrams
2018
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
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Specifically, we propose a dynamic graph-generation network that is based on dynamic memory and graph theory. ...
To tackle this problem, we propose a unified diagram-parsing network for generating knowledge from diagrams based on an object detector and a recurrent neural network designed for a graphical structure ...
(b) In the graph generation branch, we pass local features f (l) from n 2 candidates to the dynamic graph generation network (DGGN) with a global feature f (g) . ...
doi:10.1109/cvpr.2018.00438
dblp:conf/cvpr/KimYKLK18
fatcat:j5gyp63swzf35aclv2dtxzv4i4
An introduction to the NMPC-Graph as general schema for causal modelling of nonlinear, multivariate, dynamic, and recursive systems with focus on time-series prediction
[article]
2017
arXiv
pre-print
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A new modelling schema, the NMPC-graph, opens the possibility of interdisciplinary and generic nonlinear, multivariate, dynamic, and recursive causal modelling in domains where basic laws are only known ...
Further, it shows how to solve the inverse problem of deriving a nonlinear ordinary differential equation system from any NMPC-graph in conjunction with historic calibration data by means of machine learning ...
An Introduction to the NMPC-Graph as General Schema for Causal Modeling of Nonlinear, Multivariate, Dynamic, and Recursive Systems with Focus on Time-Series Prediction
I. ...
arXiv:1511.00319v3
fatcat:cshbrdjngvhkzekbqp2e4esatu
Improvement of the Reliability Graph with General Gates to Analyze the Reliability of Dynamic Systems That Have Various Operation Modes
2016
Nuclear Engineering and Technology
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In this paper, the reliability graph with general gates (RGGG) method, one of the intuitive graphical modeling methods based on Bayesian networks, is improved for the reliability analyses of dynamic systems ...
The combinatorial use of a reliability matrix with dynamic nodes is illustrated through an application to a shutdown cooling system in a nuclear power plant. ...
To keep the advantage of the RGGG method to model a system by using a one-to-one match graph from the functional block diagram, additional nodes functioning as the house events in the dynamic fault tree ...
doi:10.1016/j.net.2015.12.002
fatcat:q3djs3egwfaqhgf7vn44egpbna
Network Thermodynamics
1971
Nature
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Because the dynamical equations may be read algorithmically from the network graph, the diagrams are actually another notation for the equations themselves in much the same way as the operators of vector ...
Continuum theories use vector calculus, whose operational structure arises from point set topology, to generate partial differential field equations. ...
Because the dynamical equations may be read algorithmically from the network graph, the diagrams are actually another notation for the equations themselves in much the same way as the operators of vector ...
doi:10.1038/234393a0
fatcat:jyxn5pofwbbzfamvlehedca2mq
Network Thermodynamics
1972
Nature
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Because the dynamical equations may be read algorithmically from the network graph, the diagrams are actually another notation for the equations themselves in much the same way as the operators of vector ...
Continuum theories use vector calculus, whose operational structure arises from point set topology, to generate partial differential field equations. ...
Because the dynamical equations may be read algorithmically from the network graph, the diagrams are actually another notation for the equations themselves in much the same way as the operators of vector ...
doi:10.1038/237332a0
fatcat:u6j3yeev3vbnhmluihpk7gmfxe
Temporal Multivariate Networks
[chapter]
2014
Lecture Notes in Computer Science
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Typically, its the structure of the dynamic graph that evolves as vertices and edges are added or removed from the graph. ...
Networks that evolve over time, or dynamic graphs, have been of interest to the areas of information visualization and graph drawing for many years. ...
Size: Depending on their type, SE graphs range from a few tens of elements (UML diagrams and developer networks) to hundreds of thousands (call graphs) or even millions of elements (control-flow graphs ...
doi:10.1007/978-3-319-06793-3_8
fatcat:fdvjfwg4jvathcj2mxchrotv6y
Network Analysis and Visualisation
[chapter]
2006
Lecture Notes in Computer Science
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A workshop on Network Analysis and Visualisation was held on September 11, 2005 in Limerick Ireland, in conjunction with 2005 Graph Drawing conference. ...
layout • Matrix Layout • Generalized blockmodeling • Visualisation with additional graphical elements • Visualisation of multi-relational and dynamic networks • Dense directed network layout -Jean-Daniel ...
-Vladimir Batagelj: Some Visualization Challenges from Social Network Analysis Network = Graph + Data. The data can be measured or computed/derived from the network. ...
doi:10.1007/11618058_53
fatcat:4gghue7htraixl4mosuc4ee2tq
Semantic networks
1992
Computers and Mathematics with Applications
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general concepts and relations. ...
Unlike specialized networks and diagrams, semantic networks aim to represent any kind of knowledge which can be described in natural language. ...
as from its pure graph structure. ...
doi:10.1016/0898-1221(92)90135-5
fatcat:4nli67lrsjdzdiu56i5ixwhm2a
Network Identification Methods
[article]
2016
bioRxiv
pre-print
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This article provides a brief overview of different approaches used to identify biological networks and reviews recent advances in network identification. ...
Recently, network inference algorithms have grown tremendously in the field of systems biology because network identification is essential for understanding relationships between regulation mechanisms ...
In general, the network identification remains a difficult problem; statistical dependencies are affected by both direct and indirect path of nodal interactions; nonlinearities in the system dynamics and ...
doi:10.1101/071217
fatcat:whn3xzdiw5fhfacnigslcoq2fy
Temporal network embedding using graph attention network
2021
Complex & Intelligent Systems
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AbstractGraph convolutional network (GCN) has made remarkable progress in learning good representations from graph-structured data. ...
Furthermore, we design a TempGAN architecture which uses both adjacency and PPMI information to generate node embeddings from temporal network. ...
A brief survey on modelling of dynamic networks using dynamic graph neural networks can be found on [53] . ...
doi:10.1007/s40747-021-00332-x
fatcat:jy6q2meccnbqvjhhxkdlmmhnmm
Optimal Network Design for Consensus Formation: Wisdom of Networked Agents
2014
International Journal of Advanced Computer Science and Applications
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This suggests that both local and global topology influence the networks dynamics. ...
The wisdom of crowds refers to the phenomenon in which the collective knowledge of a community is greater than the knowledge of any individual. ...
In general, each element (node) in a network undergoes a dynamical process while coupled to other nodes. ...
doi:10.14569/ijacsa.2014.050805
fatcat:gnawvaywuzbgxnhtpwjdrrdc3a
Network, tourism
[chapter]
2015
Encyclopedia of Tourism
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Formal analysis of networks (or network analysis) began in the mathematical field of graph theory, a branch of topology. A graph is an abstract mathematical ...
In general, a network is a picture of the connections or relationships among a set of objects (people, hence stakeholder network or social network; organizations, hence organizational network; aviation ...
Pairwise relationships among actors can be arrayed in a table (called a sociomatrix) and the network diagram drawn from this information is often referred to as a sociogram. ...
doi:10.1007/978-3-319-01669-6_284-1
fatcat:su3vr44m55hyvj2qr5ovl4vhlq
Visually Exploring Large Social Networks
[chapter]
2007
Lecture Notes in Computer Science
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This PhD focuses on visualization and interaction to navigate, explore and present large social networks. ...
As social networks are graphs, their analysis is closely related to the exploration of graphs in general. There are many programs designed to support network analysis. ...
Analysts require effective tools for handling these large, rich and dynamic social networks, to perform reliable yet flexible analysis at many levels, from overviews of the whole to a detailed analysis ...
doi:10.1007/978-3-540-74800-7_59
fatcat:4g4k5ygsnvawpcdtkjnbtoovmq
Imagining Networks
2007
Zenodo
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Paper given at conference New Network Theory, Amsterdam ...
Diagrams promote inductive abstraction from deta il to general. 3. Diagrams can be superimposed and compared. 4. Scientif ic images function as apparati and results. ...
Wit h conventional graph ical forms of abstraction, diagrams remain sufficiently flexible so tha t the transfer of knowledge can take place. 6. ...
doi:10.5281/zenodo.199115
fatcat:o6g3sdrnpveq3cmrvcfizqkqvy
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