Visualization of nonlinear programming for robot motion planning. - David Hägele; Moataz Abdelaal; Ozgur S. Oguz; Marc Toussaint; Daniel Weiskopf (VINCI, 2020)

Supplemental Material for Visualization of Nonlinear Programming for Robot Motion Planning. - David Hägele; Moataz Abdelaal; Ozgur S. Oguz; Marc Toussaint; Daniel Weiskopf (DaRUS, 2020)

Uncertainty visualization: Fundamentals and recent developments. - David Hägele; Christoph Schulz 001; Cedric Beschle; Hannah Booth; Miriam Butt; Andrea Barth; Oliver Deussen; Daniel Weiskopf (it Inf. Technol., 2022)

Visual analytics for nonlinear programming in robot motion planning. - David Hägele; Moataz Abdelaal; Ozgur S. Oguz; Marc Toussaint; Daniel Weiskopf (J. Vis., 2022)

Supplemental Material for Uncertainty-Aware Multidimensional Scaling. - David Hägele; Tim Krake; Daniel Weiskopf (DaRUS, 2022)

Uncertainty-Aware Multidimensional Scaling. - David Hägele; Tim Krake; Daniel Weiskopf (IEEE Trans. Vis. Comput. Graph., 2023)

Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions. - Luca Reichmann; David Hägele; Daniel Weiskopf (LDAV, 2024)

UADAPy: An Uncertainty-Aware Visualization and Analysis Toolbox. - Patrick Paetzold; David Hägele; Marina Evers; Daniel Weiskopf; Oliver Deussen (UncertaintyVis@VIS, 2024)

Visual Compositional Data Analytics for Spatial Transcriptomics. - David Hägele; Yuxuan Tang; Daniel Weiskopf (CoRR, 2024)

Progressive Glimmer: Expanding Dimensionality in Multidimensional Scaling. - Marina Evers; David Hägele; Sören Döring; Daniel Weiskopf (CoRR, 2024)

Maximum Entropy and Quantized Metric Models for Absolute Category Ratings. - Dietmar Saupe; Krzysztof Rusek; David Hägele; Daniel Weiskopf; Lucjan Janowski (IEEE Signal Process. Lett., 2024)

Uncertainty-Aware Seasonal-Trend Decomposition Based on Loess - Supplemental Material. - Tim Krake; Daniel Klötzl; David Hägele; Daniel Weiskopf (DaRUS, 2024)

Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions. - Luca Reichmann; David Hägele; Daniel Weiskopf (DaRUS, 2024)

Uncertainty-Aware Seasonal-Trend Decomposition Based on Loess. - Tim Krake; Daniel Klötzl; David Hägele; Daniel Weiskopf (IEEE Trans. Vis. Comput. Graph., 2025)

Two Empirical Studies on Audiovisual Semiotics of Uncertainty. - Sita Vriend; David Hägele; Daniel Weiskopf (CoRR, 2025)