A generative nonparametric Bayesian model for whole genomes. - Alan Nawzad Amin; Eli N. Weinstein; Debora S. Marks (NeurIPS, 2021)

Optimal Design of Stochastic DNA Synthesis Protocols based on Generative Sequence Models. - Eli N. Weinstein; Alan Nawzad Amin; Will S. Grathwohl; Daniel Kassler; Jean Disset; Debora S. Marks (AISTATS, 2022)

Non-identifiability and the Blessings of Misspecification in Models of Molecular Fitness. - Eli N. Weinstein; Alan Nawzad Amin; Jonathan Frazer; Debora S. Marks (NeurIPS, 2022)

A Kernelized Stein Discrepancy for Biological Sequences. - Alan Nawzad Amin; Eli N. Weinstein; Debora Susan Marks (ICML, 2023)

Biological Sequence Kernels with Guaranteed Flexibility. - Alan Nawzad Amin; Eli Nathan Weinstein; Debora Susan Marks (CoRR, 2023)

Scalable and Flexible Causal Discovery with an Efficient Test for Adjacency. - Alan Nawzad Amin; Andrew Gordon Wilson (ICML, 2024)

Kernel-Based Evaluation of Conditional Biological Sequence Models. - Pierre Glaser; Steffanie Paul; Alissa M. Hummer; Charlotte M. Deane; Debora Susan Marks; Alan Nawzad Amin (ICML, 2024)

Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences. - Alan Nawzad Amin; Nate Gruver; Yilun Kuang; Yucen Lily Li; Hunter Elliott; Calvin McCarter; Aniruddh Raghu; Peyton Greenside; Andrew Gordon Wilson (ICLR, 2025)

Why Masking Diffusion Works: Condition on the Jump Schedule for Improved Discrete Diffusion. - Alan Nawzad Amin; Nate Gruver; Andrew Gordon Wilson (CoRR, 2025)

Training Flexible Models of Genetic Variant Effects from Functional Annotations using Accelerated Linear Algebra. - Alan Nawzad Amin; Andres Potapczynski; Andrew Gordon Wilson (CoRR, 2025)