15 citations · 23 across the 7 of their papers we have counts for
10 papers
A Large-Scale Sensitivity Analysis on Latent Embeddings and Dimensionality Reductions for Text Spatializations
Daniel Atzberger, Tim Cech, Willy Scheibel +3
The semantic similarity between documents of a text corpus can be visualized using map-like metaphors based on two-dimensional scatterplot layouts. These layouts result from a dime…
2D, 2.5D, or 3D? An Exploratory Study on Multilayer Network Visualisations in Virtual Reality
Stefan P. Feyer, Bruno Pinaud, Stephen G. Kobourov +6
Relational information between different types of entities is often modelled by a multilayer network (MLN) -- a network with subnetworks represented by layers. The layers of an MLN…
ShaRP: Shape-Regularized Multidimensional Projections
Alister Machado, Alexandru Telea, Michael Behrisch
Projections, or dimensionality reduction methods, are techniques of choice for the visual exploration of high-dimensional data. Many such techniques exist, each one of them having…
Visualizing Uncertainty in Sets
Christian Tominski, Michael Behrisch, Susanne Bleisch +4
Set visualization facilitates the exploration and analysis of set-type data. However, how sets should be visualized when the data is uncertain is still an open research challenge.…
PIXAL: Anomaly Reasoning with Visual Analytics
Brian Montambault, Camelia D. Brumar, Michael Behrisch +1
Anomaly detection remains an open challenge in many application areas. While there are a number of available machine learning algorithms for detecting anomalies, analysts are frequ…
PSEUDo: Interactive Pattern Search in Multivariate Time Series with Locality-Sensitive Hashing and Relevance Feedback
Yuncong Yu, Dylan Kruyff, Tim Becker +1
We present PSEUDo, an adaptive feature learning technique for exploring visual patterns in multi-track sequential data. Our approach is designed with the primary focus to overcome…