3 citations · 5 across the 3 of their papers we have counts for
4 papers
A Diffusion Model to Shrink Proteins While Maintaining Their Function
Ethan Baron, Alan N. Amin, Ruben Weitzman +2
Many proteins useful in modern medicine or bioengineering are challenging to make in the lab, fuse with other proteins in cells, or deliver to tissues in the body, because their se…
Is Sequence Information All You Need for Bayesian Optimization of Antibodies?
Sebastian W. Ober, Calvin McCarter, Aniruddh Raghu +4
Bayesian optimization is a natural candidate for the engineering of antibody therapeutic properties, which is often iterative and expensive. However, finding the optimal choice of…
Why Masking Diffusion Works: Condition on the Jump Schedule for Improved Discrete Diffusion
Alan N. Amin, Nate Gruver, Andrew Gordon Wilson
Discrete diffusion models, like continuous diffusion models, generate high-quality samples by gradually undoing noise applied to datapoints with a Markov process. Gradual generatio…
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…