Author

Oliver Deussen

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#machine learning Preprint Oct 2026

ibUMAP: Coherent and Scalable Field Evaluation for UMAP Optimization

UMAP achieves scalable layout optimization through stochastic negative sampling. However, this stochasticity can lead to unstable embeddings across reruns and downstream reuse, as the estimated repulsive forces depend on the ordering of sampling events. We present ibUMAP, a coherent field-based alternative that evaluat...

Bin Chen, Yu-Meng Xue, Patrick Paetzold et al. · 0 citations

Preprint Aug 2026

SNAP-tFDP: Massively Scalable Graph Layouts via Sparse Negative Sampling

Comprehensive evaluations on 12 large-scale graphs demonstrate that the proposed negative sampling-based algorithm outperforms state-of-the-art algorithms in neighborhood preservation and cluster separation and reduces memory consumption by 72% on average.

Xin Chen, Shuowei Hou, Yifan Wang et al. · 0 citations