# Covariance estimation using conjugate gradient for 3D classification in Cryo-EM

arXiv: https://arxiv.org/abs/1412.0985 · HTML: https://mlsanity.com/paper/1412.0985/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Dec 2014.

## Built on by (most cited first, 1 of 1)

- [SOLVAR: Fast covariance-based heterogeneity analysis with pose refinement for cryo-EM](https://mlsanity.com/paper/2602.17603/) (2026)

## Abstract (arXiv)

Classifying structural variability in noisy projections of biological macromolecules is a central problem in Cryo-EM. In this work, we build on a previous method for estimating the covariance matrix of the three-dimensional structure present in the molecules being imaged. Our proposed method allows for incorporation of contrast transfer function and non-uniform distribution of viewing angles, making it more suitable for real-world data. We evaluate its performance on a synthetic dataset and an experimental dataset obtained by imaging a 70S ribosome complex.