15 citations · 16 across the 3 of their papers we have counts for
3 papers
Visualization for Trust in Machine Learning Revisited: The State of the Field in 2023
Angelos Chatzimparmpas, Kostiantyn Kucher, Andreas Kerren
Visualization for explainable and trustworthy machine learning remains one of the most important and heavily researched fields within information visualization and visual analytics…
DimVis: Interpreting Visual Clusters in Dimensionality Reduction With Explainable Boosting Machine
Parisa Salmanian, Angelos Chatzimparmpas, Ali Can Karaca +1
Dimensionality Reduction (DR) techniques such as t-SNE and UMAP are popular for transforming complex datasets into simpler visual representations. However, while effective in uncov…
Evaluating the Utility of Conformal Prediction Sets for AI-Advised Image Labeling
Dongping Zhang, Angelos Chatzimparmpas, Negar Kamali +1
As deep neural networks are more commonly deployed in high-stakes domains, their black-box nature makes uncertainty quantification challenging. We investigate the presentation of c…