157 citations · 351 across the 20 of their papers we have counts for
5 papers · 1 filter
Visualizing Uncertainty in Non-linear Projections with Ensembles
Kai Nylund, Michael Correll, Lace Padilla
Widely used non-linear dimensionality reduction (NLDR) methods such as UMAP and t-SNE are stochastic--repeated runs on the same data can produce different low-dimensional projectio…
Seeing Through the Forecast Clutter: Communicating Climate Forecast Distributions with Weighted Multiple Forecast Visualizations
Ruishi Zou, Siyi Wu, Racquel Fygenson +3
Forecasts often diverge because different models make varying assumptions to account for underlying uncertainty. Readers who consume forecasts may wish to survey the shape and spre…
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…
"Trust Junk" Leads to Unjustified Support for Highly Discriminatory Predictive Models
Michael Correll, Lucy Havens, Mahsan Nourani
The persuasive power of data visualizations can go awry: for instance, in an explainable AI (XAI) context, visualizations can produce over-trust of predictive models. In this paper…
"The Worst Weather In America": Augmenting the Information Design of Extreme Cold Weather Forecasts
Michael Correll, Jay Broccolo, Drew Bush
Mount Washington is home to extreme, and extremely volatile, weather conditions. Consulting a weather forecast of conditions at the summit is vital for making one's visit as safe a…