no code implementations • 12 Jun 2023 • Eitan Rosen, Xiuyuan Cheng, Yoel Shkolnisky
The diffusion maps embedding of data lying on a manifold have shown success in tasks ranging from dimensionality reduction and clustering, to data visualization.
no code implementations • 29 Mar 2023 • Eitan Rosen, Paulina Hoyos, Xiuyuan Cheng, Joe Kileel, Yoel Shkolnisky
We introduce the G-invariant graph Laplacian that generalizes the graph Laplacian by accounting for the action of the group on the data set.
1 code implementation • 2 Dec 2022 • Guy Sharon, Yoel Shkolnisky, Tamir Bendory
Different tasks in the computational pipeline of single-particle cryo-electron microscopy (cryo-EM) require enhancing the quality of the highly noisy raw images.
1 code implementation • 16 Jun 2022 • Yael Harpaz, Yoel Shkolnisky
A common task in cryo-electron microscopy (cryo-EM) data processing is to compare three-dimensional density maps of macromolecules.
1 code implementation • 18 Jan 2022 • Amitay Eldar, Ido Amos, Yoel Shkolnisky
In this paper, we present ASOCEM (Automatic Segmentation Of Contaminations in cryo-EM), an automatic method to detect and segment contaminations, which requires as an input only the approximated particle size.
2 code implementations • 7 Sep 2020 • Roy Mitz, Yoel Shkolnisky
Various kernel approximation methods were proposed to overcome this issue, with the most prominent method being the Nystr{\"o}m method.
1 code implementation • 12 Dec 2019 • Amitay Eldar, Boris Landa, Yoel Shkolnisky
We present the KLT (Karhunen Loeve Transform) picker, which is fully automatic and requires as an input only the approximated particle size.
no code implementations • 25 Nov 2019 • Roy Mitz, Yoel Shkolnisky
Principal components analysis (PCA) is a fundamental algorithm in data analysis.
1 code implementation • 1 Jun 2019 • Boris Landa, Yoel Shkolnisky
Solving this problem allows to discover low-rank structures masked by the existence of translations (which act as nuisance parameters), with direct application to Principal Components Analysis (PCA).
Statistics Theory Data Structures and Algorithms Information Theory Information Theory Statistics Theory
no code implementations • 6 Feb 2018 • Boris Landa, Yoel Shkolnisky
Essentially, the steerable GL extends the standard GL by accounting for all (infinitely-many) planar rotations of all images.
no code implementations • 5 Sep 2016 • Yariv Aizenbud, Yoel Shkolnisky
In this paper, we attempt to make the first steps towards rigorous mathematical analysis of the heterogeneity problem in cryo-electron microscopy.
no code implementations • 9 Aug 2016 • Boris Landa, Yoel Shkolnisky
This paper describes a fast and accurate method for obtaining steerable principal components from a large dataset of images, assuming the images are well localized in space and frequency.
no code implementations • 28 Jun 2016 • Moshe Salhov, Ofir Lindenbaum, Yariv Aizenbud, Avi Silberschatz, Yoel Shkolnisky, Amir Averbuch
Data analysis methods aim to uncover the underlying low dimensional structure imposed by the low dimensional hidden parameters by utilizing distance metrics that consider the set of attributes as a single monolithic set.
no code implementations • 13 Feb 2016 • Leonid Gugel, Yoel Shkolnisky, Shai Dekel
In this paper we construct a learning architecture for high dimensional time series sampled by sensor arrangements.
no code implementations • 2 Dec 2014 • Zhizhen Zhao, Yoel Shkolnisky, Amit Singer
Cryo-electron microscopy nowadays often requires the analysis of hundreds of thousands of 2D images as large as a few hundred pixels in each direction.
no code implementations • 20 Nov 2014 • Victor May, Yosi Keller, Nir Sharon, Yoel Shkolnisky
We present a method for improving a Non Local Means operator by computing its low-rank approximation.