15 citations · 43 across the 12 of their papers we have counts for
12 papers
Visual Boosting Techniques for Spatiotemporal Dense Pixel Visualizations
Julius Rauscher, Frederik L. Dennig, Udo Schlegel +2
The analysis of spatiotemporal data is essential in domains such as epidemiology and environmental monitoring, where understanding the interplay between spatially distributed pheno…
Local Neighborhood Instability in Parametric Projections: Quantitative and Visual Analysis
Frederik L. Dennig, Daniel A. Keim
Parametric projections let analysts embed new points in real time, but input variations from measurement noise or data drift can produce unpredictable shifts in the 2D layout. Whet…
LCIP: Loss-Controlled Inverse Projection of High-Dimensional Image Data
Yu Wang, Frederik L. Dennig, Michael Behrisch +1
Projections (or dimensionality reduction) methods aim to map high-dimensional data to typically 2D scatterplots for visual exploration. Inverse projection methods aim…
Dissecting Atomic Facts: Visual Analytics for Improving Fact Annotations in Language Model Evaluation
Manuel Schmidt, Daniel A. Keim, Frederik L. Dennig
Factuality evaluation of large language model (LLM) outputs requires decomposing text into discrete "atomic" facts. However, existing definitions of atomicity are underspecified, w…
DE-VAE: Revealing Uncertainty in Parametric and Inverse Projections with Variational Autoencoders using Differential Entropy
Frederik L. Dennig, Daniel A. Keim
Recently, autoencoders (AEs) have gained interest for creating parametric and invertible projections of multidimensional data. Parametric projections make it possible to embed new,…
Evaluating Autoencoders for Parametric and Invertible Multidimensional Projections
Frederik L. Dennig, Nina Geyer, Daniela Blumberg +2
Recently, neural networks have gained attention for creating parametric and invertible multidimensional data projections. Parametric projections allow for embedding previously unse…
The Categorical Data Map: A Multidimensional Scaling-Based Approach
Frederik L. Dennig, Lucas Joos, Patrick Paetzold +4
Categorical data does not have an intrinsic definition of distance or order, and therefore, established visualization techniques for categorical data only allow for a set-based or…
Comparative Evaluation of Animated Scatter Plot Transitions
Nils Rodrigues, Frederik L. Dennig, Vincent Brandt +2
Scatter plots are popular for displaying 2D data, but in practice, many data sets have more than two dimensions. For the analysis of such multivariate data, it is often necessary t…
VulnEx: Exploring Open-Source Software Vulnerabilities in Large Development Organizations to Understand Risk Exposure
Frederik L. Dennig, Eren Cakmak, Henrik Plate +1
The prevalent usage of open-source software (OSS) has led to an increased interest in resolving potential third-party security risks by fixing common vulnerabilities and exposures…
Communication Analysis through Visual Analytics: Current Practices, Challenges, and New Frontiers
Maximilian T. Fischer, Frederik L. Dennig, Daniel Seebacher +2
The automated analysis of digital human communication data often focuses on specific aspects such as content or network structure in isolation. This can provide limited perspective…
Slope-Dependent Rendering of Parallel Coordinates to Reduce Density Distortion and Ghost Clusters
David Pomerenke, Frederik L. Dennig, Daniel A. Keim +2
Parallel coordinates are a popular technique to visualize multi-dimensional data. However, they face a significant problem influencing the perception and interpretation of patterns…
FDive: Learning Relevance Models using Pattern-based Similarity Measures
Frederik L. Dennig, Tom Polk, Zudi Lin +3
The detection of interesting patterns in large high-dimensional datasets is difficult because of their dimensionality and pattern complexity. Therefore, analysts require automated…