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Michal Kmicikiewicz

2 accepted papers

2026

PepCompass: Navigating Peptide Embedding Spaces Using Riemannian Geometry

ICML 2026poster

Antimicrobial peptide discovery is challenged by the astronomical size of peptide space and the relative scarcity of active peptides. While generative models provide latent maps of this space, they typically ignore decoder-induced geometry and rely on flat Euclidean metrics, making exploration disto…

Cited by 0SourceScholar
2025

ProSpero: Active Learning for Robust Protein Design Beyond Wild-Type Neighborhoods

NeurIPS 2025poster

Designing protein sequences of both high fitness and novelty is a challenging task in data-efficient protein engineering. Exploration beyond wild-type neighborhoods often leads to biologically implausible sequences or relies on surrogate models that lose fidelity in novel regions. Here, we propose P…

Cited by 0SourceScholar