Selecting relevant data subsets from large, unfamiliar datasets can be
d...
Causal inference is a statistical paradigm for quantifying causal effect...
Natural language (NL) toolkits enable visualization developers, who may ...
Natural experiments are observational studies where the assignment of
tr...
Human biases impact the way people analyze data and make decisions. Rece...
Visual data analysis tools provide people with the agency and flexibilit...
Machine learning (ML) models are constructed by expert ML practitioners ...
Root cause analysis is a common data analysis task. While question-answe...
Mixed-initiative visual analytics systems incorporate well-established d...
With the recent release of AI interaction guidelines from Apple, Google,...
This paper systematically derives design dimensions for the structured
e...
Most visual analytics systems assume that all foraging for data happens
...
Many researchers have explored tools that aim to recommend data insights...
While many visualization researchers have attempted to define data insig...
Modern automobiles have evolved from just being mechanical machines to h...
Biologists often perform clustering analysis to derive meaningful patter...
We investigate direct manipulation of graphical encodings as a method fo...
Emotions play a key role in human communication and public presentations...
Topic modeling is commonly used to analyze and understand large document...
Visualization tools usually leverage a single interaction paradigm (e.g....
A recent advancement in the machine learning community is the developmen...
We present an exploratory study comparing the visualization construction...
Visualizations of tabular data are widely used; understanding their
effe...
Visualizations of tabular data are widely used; understanding their
effe...
Static visualizations have analytic and expressive value. However, many
...