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On Quality Indicators for Progressive Visual Analytics
(The Eurographics Association, 2019)
A key component in using Progressive Visual Analytics (PVA) is to be able to gauge the quality of intermediate analysis outcomes. This is necessary in order to decide whether a current partial outcome is already good enough ...
Visual Predictive Analytics using iFuseML
(The Eurographics Association, 2018)
Solving a predictive analytics problem involves multiple machine learning tasks in a workflow. Directing such workflows efficiently requires an understanding of data so as to identify and handle missing values and outliers, ...
Immersive Analytics of Heterogeneous Biological Data Informed through Need-finding Interviews
(The Eurographics Association, 2021)
The goal of this work is to improve existing biological analysis processes by means of immersive analytics. In a first step, we conducted need-finding interviews with 12 expert biologists to understand the limits of current ...
ScrutinAI: A Visual Analytics Approach for the Semantic Analysis of Deep Neural Network Predictions
(The Eurographics Association, 2022)
We present ScrutinAI, a Visual Analytics approach to exploit semantic understanding for deep neural network (DNN) predictions analysis, focusing on models for object detection and semantic segmentation. Typical fields of ...
A Comprehensive Workflow for Effective Imitation and Reinforcement Learning with Visual Analytics
(The Eurographics Association, 2022)
Multiple challenges hinder the application of reinforcement learning algorithms in experimental and real-world use cases even with recent successes in such areas. Such challenges occur at different stages of the development ...
ChatKG: Visualizing Temporal Patterns as Knowledge Graph
(The Eurographics Association, 2023)
Line-chart visualizations of temporal data enable users to identify interesting patterns for the user to inquire about. Using oracles, such as chat AIs, Visual Analytic tools can automatically uncover explicit knowledge ...
Nonparametric Dimensionality Reduction Quality Assessment based on Sortedness of Unrestricted Neighborhood
(The Eurographics Association, 2023)
High-dimensional data are known to be challenging to explore visually. Dimensionality Reduction (DR) techniques are good options for making high-dimensional data sets more interpretable and computationally tractable. An ...
Quantifying Uncertainty in Multivariate Time Series Pre-Processing
(The Eurographics Association, 2019)
In multivariate time series analysis, pre-processing is integral for enabling analysis, but inevitably introduces uncertainty into the data. Enabling the assessment of the uncertainty and allowing uncertainty-aware analysis, ...
Combining Cluster and Outlier Analysis with Visual Analytics
(The Eurographics Association, 2017)
Cluster and outlier analysis are two important tasks. Due to their nature these tasks seem to be opposed to each other, i.e., data objects either belong to a cluster structure or a sparsely populated outlier region. In ...