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20212026
most citedExpectation-maximization for structure determination directly from cryo-EM micrographs

4 citations · 4 across the 6 of their papers we have counts for

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eess.SP2026

A Fast Approximate Maximum Likelihood Estimator for Low SNR Multi-Reference Alignment

Shay Kreymer, Amnon Balanov, Tamir Bendory

Motivated by single-particle cryo-electron microscopy, multi-reference alignment (MRA) models the task of recovering an unknown signal from multiple noisy observations corrupted by…

eess.SP2025

Solving ill-conditioned polynomial equations using score-based priors with application to multi-target detection

Rafi Beinhorn, Shay Kreymer, Amnon Balanov +3

Recovering signals from low-order moments is a fundamental yet notoriously difficult task in inverse problems. This recovery process often reduces to solving ill-conditioned system…

eess.SP2025

A note on the sample complexity of multi-target detection

Amnon Balanov, Shay Kreymer, Tamir Bendory

This work studies the sample complexity of the multi-target detection (MTD) problem, which involves recovering a signal from a noisy measurement containing multiple instances of a…

eess.SP2023

Score-based diffusion priors for multi-target detection

Alon Zabatani, Shay Kreymer, Tamir Bendory

Multi-target detection (MTD) is the problem of estimating an image from a large, noisy measurement that contains randomly translated and rotated copies of the image. Motivated by t…

eess.SP2021

An approximate expectation-maximization for two-dimensional multi-target detection

Shay Kreymer, Amit Singer, Tamir Bendory

We consider the two-dimensional multi-target detection (MTD) problem of estimating a target image from a noisy measurement that contains multiple copies of the image, each randomly…

eess.SP2021

Generalized autocorrelation analysis for multi-target detection

Ye'Ela Shalit, Ran Weber, Asaf Abas +2

We study the multi-target detection problem of recovering a target signal from a noisy measurement that contains multiple copies of the signal at unknown locations. Motivated by th…