192 citations · 505 across the 34 of their papers we have counts for
36 papers
A Scoping Review of Mixed Initiative Visual Analytics in the Automation Renaissance
Shayan Monadjemi, Yuhan Guo, Kai Xu +2
Artificial agents are increasingly integrated into data analysis workflows, carrying out tasks that were primarily done by humans. Our research explores how the introduction of aut…
VAE Explainer: Supplement Learning Variational Autoencoders with Interactive Visualization
Donald Bertucci, Alex Endert
Variational Autoencoders are widespread in Machine Learning, but are typically explained with dense math notation or static code examples. This paper presents VAE Explainer, an int…
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…