3 papers
cs.LG2026
How to make the most of your masked language model for protein engineering
Calvin McCarter, Nick Bhattacharya, Sebastian W. Ober +1
A plethora of protein language models have been released in recent years. Yet comparatively little work has addressed how to best sample from them to optimize desired biological pr…
cs.LG2025
Unmasking Trees for Tabular Data
Calvin McCarter
Despite much work on advanced deep learning and generative modeling techniques for tabular data generation and imputation, traditional methods have continued to win on imputation b…
stat.ML2024
Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences
Alan Nawzad Amin, Nate Gruver, Yilun Kuang +6
To build effective therapeutics, biologists iteratively mutate antibody sequences to improve binding and stability. Proposed mutations can be informed by previous measurements or b…