collaborators

6 papers

cs.HC2026

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…

cs.CV2026

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…

cs.HC2026

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…

cs.LG2026

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…

cs.LG2025

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,…

cs.HC2025

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…