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Found 2 papers, 2 papers with code
ScatterUQ: Interactive Uncertainty Visualizations for Multiclass Deep Learning Problems
ScatterUQ leverages recent advances in distance-aware neural networks, together with dimensionality reduction techniques, to construct robust, 2-D scatter plots explaining why a model predicts a test example to be (1) in-distribution and of a particular class, (2) in-distribution but unsure of the class, and (3) out-of-distribution.
Knowledge Graphs in Practice: Characterizing their Users, Challenges, and Visualization Opportunities
This study presents insights from interviews with nineteen Knowledge Graph (KG) practitioners who work in both enterprise and academic settings on a wide variety of use cases.
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