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pro vyhledávání: '"Brumar, Camelia D."'
Despite decision-making being a vital goal of data visualization, little work has been done to differentiate decision-making tasks within the field. While visualization task taxonomies and typologies exist, they often focus on more granular analytica
Externí odkaz:
http://arxiv.org/abs/2404.08812
Autor:
Montambault, Brian, Appleby, Gabriel, Rogers, Jen, Brumar, Camelia D., Li, Mingwei, Chang, Remco
Dimensionality reduction techniques are widely used for visualizing high-dimensional data. However, support for interpreting patterns of dimension reduction results in the context of the original data space is often insufficient. Consequently, users
Externí odkaz:
http://arxiv.org/abs/2404.07386
Autor:
Brumar, Camelia D., Appleby, Gabriel, Rogers, Jen, Matinde, Teddy, Thompson, Lara, Chang, Remco, Crisan, Anamaria
Content recommendation tasks increasingly use Graph Neural Networks, but it remains challenging for machine learning experts to assess the quality of their outputs. Visualization systems for GNNs that could support this interrogation are few. Moreove
Externí odkaz:
http://arxiv.org/abs/2310.11562
Anomaly detection remains an open challenge in many application areas. While there are a number of available machine learning algorithms for detecting anomalies, analysts are frequently asked to take additional steps in reasoning about the root cause
Externí odkaz:
http://arxiv.org/abs/2205.11004
Autor:
Loewke, Kevin, Cho, Justina Hyunjii, Brumar, Camelia D., Maeder-York, Paxton, Barash, Oleksii, Malmsten, Jonas E., Zaninovic, Nikica, Sakkas, Denny, Miller, Kathleen A., Levy, Michael, VerMilyea, Matthew David
Publikováno v:
In Fertility and Sterility March 2022 117(3):528-535
Akademický článek
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Akademický článek
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Publikováno v:
IEEE transactions on visualization and computer graphics [IEEE Trans Vis Comput Graph] 2024 Sep 23; Vol. PP. Date of Electronic Publication: 2024 Sep 23.