collaborators

5 papers

cs.HC2026

Mixed Uncertainty in One View: Co-Visualizing Statistical Variability and Qualitative Confidence

Racquel Fygenson, Lace Padilla, Laura E. Matzen

Forecasting involves multiple forms of uncertainty, including both uncertainties that can be quantified directly (quantitative uncertainty) and those that must be expressed through…

cs.HC2026

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…

cs.HC2026

Croissant Charts: Modulating the Performance of Normal Distribution Visualizations with Affordances

Racquel Fygenson, Enrico Bertini, Lace M. Padilla

Affordances, originating in psychology, describe how an object's design influences the physical and cognitive actions users may take. Past work applied affordance theory to visuali…

cs.HC2026

Cognitive Affordances in Visualization: Related Constructs, Design Factors, and Framework

Racquel Fygenson, Lace Padilla, Enrico Bertini

Classically, affordance research investigates how the shape of objects communicates actions to potential users. Cognitive affordances, a subset of this research, characterize how t…

cs.HC2025

Set Visualizations for Comparing and Evaluating Machine Learning Models

Liudas Panavas, Tarik Crnovrsanin, Racquel Fygenson +4

Machine learning practitioners often need to compare multiple models to select the best one for their application. However, current methods of comparing models fall short because t…