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pro vyhledávání: '"Abigail Mosca"'
Autor:
Dylan Cashman, Genevieve Patterson, Nathan Watts, Abigail Mosca, Remco Chang, Shannon Robinson
Publikováno v:
IEEE Computer Graphics and Applications. 38:39-50
We present RNNbow, an interactive tool for visualizing the gradient flow during backpropagation in training of recurrent neural networks. By visualizing the gradient, as opposed to activations, RNNbow offers insight into how the network is learning.
Publikováno v:
IEEE transactions on visualization and computer graphics.
When inspecting information visualizations under time critical settings, such as emergency response or monitoring the heart rate in a surgery room, the user only has a small amount of time to view the visualization “at a glance”. In these setting
Autor:
Abigail Mosca, Kendall Park, Subhajit Das, Shah Rukh Humayoun, John Thompson, Florian Heimerl, Michael Gleicher, John Stasko, Bahador Saket, Remco Chang, Alex Endert, Dylan Cashman
Many visual analytics systems allow users to interact with machine learning models towards the goals of data exploration and insight generation on a given dataset. However, in some situations, insights may be less important than the production of an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e7029c367c16b97a8890600c7a036724
This new report examines the progress Balancing Incentive Program states have made in increasing the share of their long-term services and supports (LTSS) dollars spent on community-based services. The findings suggest that participating states incre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______645::b33117a8fa541a6a19579ebcaf03c2a3
https://www.mathematica-mpr.com/-/media/publications/pdfs/health/mfpfieldrpt18.pdf
https://www.mathematica-mpr.com/-/media/publications/pdfs/health/mfpfieldrpt18.pdf