3 papers
cs.LG2026
A Spectral Framework for Multi-Scale Nonlinear Dimensionality Reduction
Zeyang Huang, Angelos Chatzimparmpas, Thomas Höllt +1
Dimensionality reduction (DR) is characterized by two longstanding trade-offs. First, there is a global-local preservation tension: methods such as t-SNE and UMAP prioritize local…
cs.CV2026
Manifold-Preserving Superpixel Hierarchies and Embeddings for the Exploration of High-Dimensional Images
Alexander Vieth, Boudewijn Lelieveldt, Elmar Eisemann +2
High-dimensional images, or images with a high-dimensional attribute vector per pixel, are commonly explored with coordinated views of a low-dimensional embedding of the attribute…
cs.HC2024
AI-in-the-loop: The future of biomedical visual analytics applications in the era of AI
Katja Bühler, Thomas Höllt, Thomas Schulz +1
AI is the workhorse of modern data analytics and omnipresent across many sectors. Large Language Models and multi-modal foundation models are today capable of generating code, char…