2 citations · 5 across the 3 of their papers we have counts for
3 papers
FORBID: Fast Overlap Removal By stochastic gradIent Descent for Graph Drawing
Loann Giovannangeli, Frederic Lalanne, Romain Giot +1
While many graph drawing algorithms consider nodes as points, graph visualization tools often represent them as shapes. These shapes support the display of information such as labe…
Deep Neural Network for DrawiNg Networks, (DNN)^2
Loann Giovannangeli, Frederic Lalanne, David Auber +2
By leveraging recent progress of stochastic gradient descent methods, several works have shown that graphs could be efficiently laid out through the optimization of a tailored obje…
Impacts of the Numbers of Colors and Shapes on Outlier Detection: from Automated to User Evaluation
Loann Giovannangeli, Romain Giot, David Auber +1
The design of efficient representations is well established as a fruitful way to explore and analyze complex or large data. In these representations, data are encoded with various…