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Found 3 papers, 1 papers with code
State of the Art of Visual Analytics for eXplainable Deep Learning
The survey concludes by identifying future research challenges and bridging activities that are helpful to strengthen the role of Visual Analytics as effective support for eXplainable Deep Learning and to foster the adoption of Visual Analytics solutions in the eXplainable Deep Learning community.
Deep Neural Network for DrawiNg Networks, (DNN)^2
We demonstrate that it is possible to use DL techniques to learn a graph-to-layout sequence of operations thanks to a graph-related objective function.
Impacts of the Numbers of Colors and Shapes on Outlier Detection: from Automated to User Evaluation
When encoded with one attribute, the difficulty depends on that attribute heterogeneity until its capacity limit (7 for color, 5 for shape) is reached.
