Günter Klambauer

This paper develops novel base editors by diversifying TadA orthologs and using generative models to optimize specificity and efficiency.

CLOOME enables querying bioimaging databases with chemical structures using contrastive learning, achieving >70x higher accuracy than random baseline.

immuneML provides an open-source ecosystem for reproducible and interoperable machine learning analysis of adaptive immune receptor repertoires, demonstrating its utility through benchmarking and novel methods.

Transformer attention is recast as the update rule of modern Hopfield networks, and the resulting DeepRC classifier handles immune repertoires with enormous instance counts and few informative sequences.