Eli N. Weinstein

According to our database, Eli N. Weinstein authored at least 11 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Hierarchical Causal Models.

Eli N. Weinstein, David M. Blei

J. Mach. Learn. Res., 2026

2025

Accelerated Learning on Large Scale Screens using Generative Library Models.

Eli N. Weinstein, Andrei Slabodkin, Mattia G. Gollub, Elizabeth B. Wood

CoRR, October, 2025

Biological Sequence Kernels with Guaranteed Flexibility.

Alan Nawzad Amin, Debora S. Marks, Eli N. Weinstein

J. Mach. Learn. Res., 2025

2024

Estimating the Causal Effects of T Cell Receptors.

Eli N. Weinstein, Elizabeth B. Wood, David M. Blei

CoRR, 2024

2023

Bayesian Data Selection.

Eli N. Weinstein, Jeffrey W. Miller

J. Mach. Learn. Res., 2023

A Kernelized Stein Discrepancy for Biological Sequences.

Alan Nawzad Amin, Eli N. Weinstein, Debora Susan Marks

Proceedings of the International Conference on Machine Learning, 2023

2022

ProGen2: Exploring the Boundaries of Protein Language Models.

Erik Nijkamp, Jeffrey A. Ruffolo, Eli N. Weinstein, Nikhil Naik, Ali Madani

CoRR, 2022

Non-identifiability and the Blessings of Misspecification in Models of Molecular Fitness.

Eli N. Weinstein, Alan Nawzad Amin, Jonathan Frazer, Debora S. Marks

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

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

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

A generative nonparametric Bayesian model for whole genomes.

Alan Nawzad Amin, Eli N. Weinstein, Debora S. Marks

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Structured Observation Distribution for Generative Biological Sequence Prediction and Forecasting.

Eli N. Weinstein, Debora S. Marks

Proceedings of the 38th International Conference on Machine Learning, 2021