activity
20242026
collaborators

6 papers

cs.AI2026

Position: agentic AI orchestration should be Bayes-consistent

Theodore Papamarkou, Pierre Alquier, Matthias Bauer +27

LLMs excel at predictive tasks and complex reasoning tasks, but many high-value deployments rely on decisions under uncertainty, for example, which tool to call, which expert to co…

cs.LG2026

A Unification of Discrete, Gaussian, and Simplicial Diffusion

Nuria Alina Chandra, Yucen Lily Li, Alan N. Amin +5

To model discrete sequences such as DNA, proteins, and language using diffusion, practitioners must choose between three major methods: diffusion in discrete space, Gaussian diffus…

cs.LG2025

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…

cs.LG2025

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…

cs.LG2025

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…

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…