49 citations · 61 across the 8 of their papers we have counts for
9 papers
XALIGN: A Human-centric Visual Analytics Approach to Understanding AI Explanations
Bahavathy Kathirgamanathan, Gennady Andrienko, Natalia Andrienko +1
Explainable AI (XAI) methods are usually evaluated for technical properties such as faithfulness and robustness. In high-stakes application domains, experts also need to check mode…
Understanding How Humans Inject Knowledge into Machine Learning Workflows through Visual Analytics
Yiwen Xing, Philip Beaucamp, Joyraj Chakraborty +6
Visual analytics (VA) plays an increasingly important role in supporting machine learning (ML) workflows. In the field of visualization, such approaches and techniques are referred…
From Idea to Prototype in an Afternoon: Scaffolded, AI-Assisted Rapid VA Prototyping
Gennady Andrienko, Natalia Andrienko
Testing a new visual-analytics idea usually takes months: one needs to find a realistic data set, clean it, and implement an interactive prototype. We describe a case where a workf…
SmartIterator: Visual Analytics Workflows for Supervising Unsupervised Data Grouping
Gennady Andrienko, Natalia Andrienko
Unsupervised learning methods -- topic modeling, partition-based and density-based clustering -- produce data groupings without human guidance, yet choosing and evaluating those gr…
ATWL: A Formal Language for Representing, Comparing, and Reusing Visual Analytics Workflows
Natalia Andrienko, Gennady Andrienko, Jürgen Bernard +2
Visual analytics (VA) workflows combine data transformation, feature computation, visual representation, and human interpretation, but they are usually described in prose. This hin…
Towards Mobility Data Science (Vision Paper)
Mohamed Mokbel, Mahmoud Sakr, Li Xiong +45
Mobility data captures the locations of moving objects such as humans, animals, and cars. With the availability of GPS-equipped mobile devices and other inexpensive location-tracki…
Give more data, awareness and control to individual citizens, and they will help COVID-19 containment
Mirco Nanni, Gennady Andrienko, Albert-László Barabási +36
The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the phase 2 of the pandemic, when…
Resolving Congestions in the Air Traffic Management Domain via Multiagent Reinforcement Learning Methods
Theocharis Kravaris, Christos Spatharis, Alevizos Bastas +5
In this article, we report on the efficiency and effectiveness of multiagent reinforcement learning methods (MARL) for the computation of flight delays to resolve congestion proble…
Applications of Trajectory Data from the Perspective of a Road Transportation Agency: Literature Review and Maryland Case Study
Nikola Marković, Przemysław Sekuła, Zachary Vander Laan +2
Transportation agencies have an opportunity to leverage increasingly-available trajectory datasets to improve their analyses and decision-making processes. However, this data is ty…