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Martin Steinegger

2 accepted papers

2026

One protein is all you need

ICLR 2026poster

Generalization beyond training data remains a central challenge in machine learning for biology. A common way to enhance generalization is self-supervised pre-training on large datasets. However, aiming to perform well on all possible proteins can limit a model’s capacity to excel on any specific on…

Cited by 0SourcecodeScholar
2026

Scaling Atomistic Protein Binder Design with Generative Pretraining and Test-Time Compute

ICLR 2026oral

Protein interaction modeling is central to protein design, which has been transformed by machine learning with broad applications in drug discovery and beyond. In this landscape, structure-based de novo binder design is most often cast as either conditional generative modeling or sequence optimizati…

Cited by 0SourcecodeScholar