activity
20182024
most citedSemi-supervised Learning in Network-Structured Data via Total Variation Minimization

38 citations · 66 across the 5 of their papers we have counts for

collaborators

7 papers

q-bio.QM2024

Outlier Removal in Cryo-EM via Radial Profiles

Lev Kapnulin, Ayelet Heimowitz, Nir Sharon

The process of particle picking, a crucial step in cryo-electron microscopy (cryo-EM) image analysis, often encounters challenges due to outliers, leading to inaccuracies in downst…

cs.CV2023★ 23 cited

Image Segmentation via Probabilistic Graph Matching

Ayelet Heimowitz, Yosi Keller

This work presents an unsupervised and semi-automatic image segmentation approach where we formulate the segmentation as a inference problem based on unary and pairwise assignment…

eess.IV2020

Centering noisy images with application to cryo-EM

Ayelet Heimowitz, Nir Sharon, Amit Singer

We target the problem of estimating the center of mass of noisy 2-D images. We assume that the noise dominates the image, and thus many standard approaches are vulnerable to estima…

eess.IV2019

Bias and variance reduction and denoising for CTF Estimation

Ayelet Heimowitz, Joakim Andén, Amit Singer

When using an electron microscope for imaging of particles embedded in vitreous ice, the objective lens will inevitably corrupt the projection images. This corruption manifests as…

cs.LG2019★ 38 cited

Semi-supervised Learning in Network-Structured Data via Total Variation Minimization

Alexander Jung, Alfred O. Hero, Alexandru Mara +3

We propose and analyze a method for semi-supervised learning from partially-labeled network-structured data. Our approach is based on a graph signal recovery interpretation under a…

eess.SP2018★ 5 cited

A Markov Variation Approach to Smooth Graph Signal Interpolation

Ayelet Heimowitz, Yonina C. Eldar

In this paper we present the Markov variation, a smoothness measure which offers a probabilistic interpretation of graph signal smoothness. This measure is then used to develop an…