Author

R. Eils

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Jul 2026

Beyond Objective Expressivity: Geometry Preservation in Multimodal Contrastive Learning

This work introduces geometry-preserving encoders (GPEs) by directly conditioning the Jacobian through regularization and demonstrating that simple modifications like LeakyReLU activations and residual paths recover these geometric benefits.

Tillmann Rheude, R. Eils, B. Wild · arXiv.org · 0 citations

Open access Jul 2026

An interpretable omnigenic neural network architecture for the human genome

Genetic prediction of complex phenotypes typically relies on additive linear models, which scale well but cannot capture non-additive effects or deeply integrate molecular and clinical data. Domain-specific neural networks have driven advances in images, text, and other modalities, but genome-scale neural networks rema...

J. Upmeier zu Belzen, L. Arnoldt, N. Hollmann et al. · medRxiv · 0 citations