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cs.LG2026
Mol-JEPA: A multimodal Joint Embedding Predictive Architecture for Molecules
Florian Rottach, Sebastian Schieferdecker, William Rudman +2
Despite recent advances in molecular foundation models, several limitations remain, such as chemically invalid augmentations, modality collapse, and incomplete representation of bi…
cs.LG2025
From Topology to Retrieval: Decoding Embedding Spaces with Unified Signatures
Florian Rottach, William Rudman, Bastian Rieck +2
Studying how embeddings are organized in space not only enhances model interpretability but also uncovers factors that drive downstream task performance. In this paper, we present…
cs.LG2025
Molecular Machine Learning Using Euler Characteristic Transforms
Victor Toscano-Duran, Florian Rottach, Bastian Rieck
The shape of a molecule determines its physicochemical and biological properties. However, it is often underrepresented in standard molecular representation learning approaches. He…