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      Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow

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          The complexity of theorem-proving procedures

           Stephen Cook (1971)
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            D³: Data-Driven Documents.

            Data-Driven Documents (D3) is a novel representation-transparent approach to visualization for the web. Rather than hide the underlying scenegraph within a toolkit-specific abstraction, D3 enables direct inspection and manipulation of a native representation: the standard document object model (DOM). With D3, designers selectively bind input data to arbitrary document elements, applying dynamic transforms to both generate and modify content. We show how representational transparency improves expressiveness and better integrates with developer tools than prior approaches, while offering comparable notational efficiency and retaining powerful declarative components. Immediate evaluation of operators further simplifies debugging and allows iterative development. Additionally, we demonstrate how D3 transforms naturally enable animation and interaction with dramatic performance improvements over intermediate representations. © 2010 IEEE
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              Methods for Visual Understanding of Hierarchical System Structures

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                Author and article information

                Journal
                IEEE Transactions on Visualization and Computer Graphics
                IEEE Trans. Visual. Comput. Graphics
                Institute of Electrical and Electronics Engineers (IEEE)
                1077-2626
                January 2018
                January 2018
                : 24
                : 1
                : 1-12
                Article
                10.1109/TVCG.2017.2744878
                © 2018
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