Results 11 to 20 of about 1,258,420 (289)
Acyclic Partitioning of Large Directed Acyclic Graphs [PDF]
2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), 2017 Finding a good partition of a computational directed acyclic graph associated with an algorithm can help find an execution pattern improving data locality, conduct an analysis of data movement, and expose parallel steps. The partition is required to be acyclic, i.e., the inter-part edges between the vertices from different parts should preserve an ...
Herrmann, Julien +4 more
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Statistical tests for associations between two directed acyclic graphs. [PDF]
PLoS ONE, 2010 Biological data, and particularly annotation data, are increasingly being represented in directed acyclic graphs (DAGs). However, while relevant biological information is implicit in the links between multiple domains, annotations from these different ...
Robert Hoehndorf +3 more
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Collapsibility for Directed Acyclic Graphs
Scandinavian Journal of Statistics, 2009 Abstract. Collapsibility means that the same statistical result of interest can be obtained before and after marginalization over some variables. In this paper, we discuss three kinds of collapsibility for directed acyclic graphs (DAGs): estimate collapsibility, conditional independence collapsibility and model collapsibility. Related to collapsibility,
Xie, Xianchao, Geng, Zhi
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This source code implements a unified framework for pre-processing Directed Acyclic Graphs (DAGs) to lookup reachability between two vertices as well as compute the least upper bound of two vertices in constant time.
Dominique Haughton +2 more
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Tutorial on directed acyclic graphs. [PDF]
J Clin Epidemiol, 2022 Directed acyclic graphs (DAGs) are an intuitive yet rigorous tool to communicate about causal questions in clinical and epidemiologic research and inform study design and statistical analysis. DAGs are constructed to depict prior knowledge about biological and behavioral systems related to specific causal research questions.
Digitale JC, Martin JN, Glymour MM.
europepmc +5 more sources
Contextual Directed Acyclic Graphs
CoRR, 2023 To appear in the Proceedings of the 27th International Conference on Artificial Intelligence and ...
Ryan Thompson +2 more
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Directed Acyclic Graphs With Tears
IEEE Transactions on Artificial Intelligence, 2023 Bayesian network is a frequently-used method for fault detection and diagnosis in industrial processes. The basis of Bayesian network is structure learning which learns a directed acyclic graph (DAG) from data. However, the search space will scale super-exponentially with the increase of process variables, which makes the data-driven structure learning
Zhichao Chen 0001, Zhiqiang Ge
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Copula Directed Acyclic Graphs [PDF]
SSRN Electronic Journal, 2015 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Pircalabelu, Eugen +2 more
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A directed acyclic graph for interactions [PDF]
International Journal of Epidemiology, 2020 Abstract Background Directed acyclic graphs (DAGs) are of great help when researchers try to understand the nature of causal relationships and the consequences of conditioning on different variables.
Anton Nilsson +3 more
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Treemaps for Directed Acyclic Graphs [PDF]
, 2008 Gene Ontology information related to the biological role of genes is organized in a hierarchical manner that can be represented by a directed acyclic graph (DAG). Treemaps graphically represent hierarchical information via a two-dimensional rectangular map. They efficiently display large trees in limited screen space.
Vassilis Tsiaras +2 more
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