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Eli N. Weinstein
Eli N. Weinstein
Postdoctoral Research Scientist, Data Science Institute, Columbia University
Verified email at columbia.edu - Homepage
Title
Cited by
Cited by
Year
ProGen2: exploring the boundaries of protein language models
E Nijkamp, JA Ruffolo, EN Weinstein, N Naik, A Madani
Cell Systems 14 (11), 968-978. e3, 2023
3012023
Genetically targeted all-optical electrophysiology with a transgenic Cre-dependent optopatch mouse
S Lou, Y Adam, EN Weinstein, E Williams, K Williams, V Parot, ...
Journal of Neuroscience 36 (43), 11059-11073, 2016
1012016
All-optical electrophysiology for high-throughput functional characterization of a human iPSC-derived motor neuron model of ALS
E Kiskinis, JM Kralj, P Zou, EN Weinstein, H Zhang, K Tsioras, O Wiskow, ...
Stem cell reports 10 (6), 1991-2004, 2018
662018
Co-evolution of interacting proteins through non-contacting and non-specific mutations
D Ding, AG Green, B Wang, TLV Lite, EN Weinstein, DS Marks, MT Laub
Nature Ecology & Evolution 6 (5), 590-603, 2022
402022
Non-identifiability and the Blessings of Misspecification in Models of Molecular Fitness
EN Weinstein, AN Amin, J Frazer, DS Marks
Advances in Neural Information Processing Systems, 2022
252022
Optimal Design of Stochastic DNA Synthesis Protocols based on Generative Sequence Models
EN Weinstein, AN Amin, W Grathwohl, D Kassler, J Disset, DS Marks
International Conference on Artificial Intelligence and Statistics 151, 7450 …, 2022
242022
A structured observation distribution for generative biological sequence prediction and forecasting
EN Weinstein, DS Marks
International Conference on Machine Learning (ICML) 38, 11068-11079, 2021
152021
A generative nonparametric Bayesian model for whole genomes
A Amin, EN Weinstein, D Marks
Advances in Neural Information Processing Systems 34, 27798-27812, 2021
122021
Generative Models for Codon Prediction and Optimization
DK Yang, SL Goldman, E Weinstein, D Marks
Machine Learning in Computational Biology, 2019
72019
Biological Sequence Kernels with Guaranteed Flexibility
AN Amin, EN Weinstein, DS Marks
arXiv preprint arXiv:2304.03775, 2023
62023
Bayesian data selection
EN Weinstein, JW Miller
Journal of Machine Learning Research 24 (23), 1-72, 2023
62023
A Kernelized Stein Discrepancy for Biological Sequences
AN Amin, EN Weinstein, DS Marks
International Conference on Machine Learning, 2023
52023
Generative Statistical Methods for Biological Sequences
EN Weinstein
Harvard University, 2022
52022
Hierarchical Causal Models
EN Weinstein, DM Blei
arXiv preprint arXiv:2401.05330, 2024
32024
Manufacturing-Aware Generative Model Architectures Enable Biological Sequence Design and Synthesis at Petascale
EN Weinstein, MG Gollub, A Slabodkin, CL Gardner, K Dobbs, XB Cui, ...
bioRxiv, 2024.09. 13.612900, 2024
32024
Estimating the Causal Effects of T Cell Receptors
EN Weinstein, EB Wood, DM Blei
arXiv preprint arXiv:2410.14127, 2024
12024
Adaptive Nonparametric Perturbations of Parametric Bayesian Models
B Wu, EN Weinstein, S Salehi, Y Wang, DM Blei
arXiv preprint arXiv:2412.10683, 2024
2024
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