In the intricate dance of balancing efficiency and performance within AI projects, the selection among sparse, small and large models isn't just a technical decision—it's a strategic imperative that ...

Factoring out nucleotide-level mutation biases from antibody language models dramatically improves prediction of functional mutation effects while reducing computational cost by orders of magnitude.

The development of robust clinical trial methodologies increasingly relies on advanced statistical frameworks for model selection and the characterisation of dose–response relationships. With modern ...