An Emergent Space for Distributed Data With Hidden Internal Order Through Manifold Learning. - Felix P. Kemeth; Sindre W. Haugland; Felix Dietrich; Tom Bertalan; Kevin Höhlein; Qianxiao Li; Erik M. Bollt; Ronen Talmon; Katharina Krischer; Ioannis G. Kevrekidis (IEEE Access, 2018)

Learning Multiple-Scattering Solutions for Sphere-Tracing of Volumetric Subsurface Effects. - Ludwig Leonard; Kevin Höhlein; Rüdiger Westermann (Comput. Graph. Forum, 2021)

Learning Multiple-Scattering Solutions for Sphere-Tracing of Volumetric Subsurface Effects. - Ludwig Leonard; Kevin Höhlein; Rüdiger Westermann (Zenodo, 2021)

Learning Multiple-Scattering Solutions for Sphere-Tracing of Volumetric Subsurface Effects. - Ludwig Leonard; Kevin Höhlein; Rüdiger Westermann (Zenodo, 2021)

Evaluation of Volume Representation Networks for Meteorological Ensemble Compression. - Kevin Höhlein; Sebastian Weiss; Rüdiger Westermann (VMV, 2022)

GPU accelerated scalable parallel coordinates plots. - Josef Stumpfegger; Kevin Höhlein; George Craig; Rüdiger Westermann (Comput. Graph., 2022)

Neural Fields for Interactive Visualization of Statistical Dependencies in 3D Simulation Ensembles. - Fatemeh Farokhmanesh; Kevin Höhlein; Christoph Neuhauser; Rüdiger Westermann (VMV, 2023)

Postprocessing of Ensemble Weather Forecasts Using Permutation-invariant Neural Networks. - Kevin Höhlein; Benedikt Schulz; Rüdiger Westermann; Sebastian Lerch (CoRR, 2023)

Topographic Visualization of Near-surface Temperatures for Improved Lapse Rate Estimation. - Kevin Höhlein; Timothy Hewson; Rüdiger Westermann (CoRR, 2024)

Learning low-dimensional representations of ensemble forecast fields using autoencoder-based methods. - Jieyu Chen; Kevin Höhlein; Sebastian Lerch (CoRR, 2025)