215 citations · 478 across the 21 of their papers we have counts for
23 papers
Charting the Moral Universe: Capturing Virtues and Values of Data Visualization Practice
Chloe Hudson Prock, Enrico Bertini, Michael Correll
What do we value in our visualizations, and in the people who design them? Despite a growing body of work on critical data visualization, the conception of what it is to do ethical…
The Arrangement of Marks Impacts Afforded Messages: Ordering, Partitioning, Spacing, and Coloring in Bar Charts
Racquel Fygenson, Steven Franconeri, Enrico Bertini
Data visualizations present a massive number of potential messages to an observer. One might notice that one group's average is larger than another's, or that a difference in value…
Misinformed by Visualization: What Do We Learn From Misinformative Visualizations?
Leo Yu-Ho Lo, Ayush Gupta, Kento Shigyo +3
Data visualization is powerful in persuading an audience. However, when it is done poorly or maliciously, a visualization may become misleading or even deceiving. Visualizations gi…
Visual Exploration of Machine Learning Model Behavior with Hierarchical Surrogate Rule Sets
Jun Yuan, Brian Barr, Kyle Overton +1
One of the potential solutions for model interpretation is to train a surrogate model: a more transparent model that approximates the behavior of the model to be explained. Typical…
An Exploration And Validation of Visual Factors in Understanding Classification Rule Sets
Jun Yuan, Oded Nov, Enrico Bertini
Rule sets are often used in Machine Learning (ML) as a way to communicate the model logic in settings where transparency and intelligibility are necessary. Rule sets are typically…
AdViCE: Aggregated Visual Counterfactual Explanations for Machine Learning Model Validation
Oscar Gomez, Steffen Holter, Jun Yuan +1
Rapid improvements in the performance of machine learning models have pushed them to the forefront of data-driven decision-making. Meanwhile, the increased integration of these mod…