27 citations · 63 across the 6 of their papers we have counts for
6 papers · 1 filter
MiMICRI: Towards Domain-centered Counterfactual Explanations of Cardiovascular Image Classification Models
Grace Guo, Lifu Deng, Animesh Tandon +2
The recent prevalence of publicly accessible, large medical imaging datasets has led to a proliferation of artificial intelligence (AI) models for cardiovascular image classificati…
What We Augment When We Augment Visualizations: A Design Elicitation Study of How We Visually Express Data Relationships
Grace Guo, John Stasko, Alex Endert
Visual augmentations are commonly added to charts and graphs in order to convey richer and more nuanced information about relationships in the data. However, many design spaces pro…
Visualizing Intelligent Tutor Interactions for Responsive Pedagogy
Grace Guo, Aishwarya Mudgal Sunil Kumar, Adit Gupta +3
Intelligent tutoring systems leverage AI models of expert learning and student knowledge to deliver personalized tutoring to students. While these intelligent tutors have demonstra…
Explainability in JupyterLab and Beyond: Interactive XAI Systems for Integrated and Collaborative Workflows
Grace Guo, Dustin Arendt, Alex Endert
Explainable AI (XAI) tools represent a turn to more human-centered and human-in-the-loop AI approaches that emphasize user needs and perspectives in machine learning model developm…
Situating Data Sets: Making Public Data Actionable for Housing Justice
Anh-Ton Tran, Grace Guo, Jordan Taylor +3
Activists, governmentsm and academics regularly advocate for more open data. But how is data made open, and for whom is it made useful and usable? In this paper, we investigate and…
Causalvis: Visualizations for Causal Inference
Grace Guo, Ehud Karavani, Alex Endert +1
Causal inference is a statistical paradigm for quantifying causal effects using observational data. It is a complex process, requiring multiple steps, iterations, and collaboration…