activity
20192026
most citedResolving Congestions in the Air Traffic Management Domain via Multiagent Reinforcement Learning Methods

6 citations · 8 across the 4 of their papers we have counts for

collaborators

6 papers

cs.HC2026

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…

cs.HC2026

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…

cs.HC2026

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…

cs.AI2026

ATWL: A Formal Language for Representing, Comparing, and Reusing Visual Analytics Workflows

Natalia Andrienko, Gennady Andrienko, Jürgen Bernard +1

Visual analytics (VA) workflows are inherently complex, involving data transformation, feature engineering, visual representation, and human interpretation. They are typically desc…

cs.CY20202 cited

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…

cs.MA20196 cited

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…