Steerable Principal Components for Space-Frequency Localized Images. - Boris Landa; Yoel Shkolnisky (SIAM J. Imaging Sci., 2017)

The steerable graph Laplacian and its application to filtering image data-sets. - Boris Landa; Yoel Shkolnisky (CoRR, 2018)

The Steerable Graph Laplacian and its Application to Filtering Image Datasets. - Boris Landa; Yoel Shkolnisky (SIAM J. Imaging Sci., 2018)

Multi-reference factor analysis: low-rank covariance estimation under unknown translations. - Boris Landa; Yoel Shkolnisky (CoRR, 2019)

Method of moments for 3-D single particle ab initio modeling with non-uniform distribution of viewing angles. - Nir Sharon; Joe Kileel 001; Yuehaw Khoo; Boris Landa; Amit Singer (CoRR, 2019)

Scaling positive random matrices: concentration and asymptotic convergence. - Boris Landa (CoRR, 2020)

Rank-one multi-reference factor analysis. - Yariv Aizenbud; Boris Landa; Yoel Shkolnisky (Stat. Comput., 2021)

Doubly Stochastic Normalization of the Gaussian Kernel Is Robust to Heteroskedastic Noise. - Boris Landa; Ronald R. Coifman; Yuval Kluger (SIAM J. Math. Data Sci., 2021)

Bi-stochastically normalized graph Laplacian: convergence to manifold Laplacian and robustness to outlier noise. - Xiuyuan Cheng; Boris Landa (CoRR, 2022)

Biwhitening Reveals the Rank of a Count Matrix. - Boris Landa; Thomas T. C. K. Zhang; Yuval Kluger (SIAM J. Math. Data Sci., 2022)

Robust Inference of Manifold Density and Geometry by Doubly Stochastic Scaling. - Boris Landa; Xiuyuan Cheng (SIAM J. Math. Data Sci., 2023)

Entropic Optimal Transport Eigenmaps for Nonlinear Alignment and Joint Embedding of High-Dimensional Datasets. - Boris Landa; Yuval Kluger; Rong Ma (CoRR, 2024)

Euclidean Distance Deflation Under High-Dimensional Heteroskedastic Noise. - Keyi Li; Yuval Kluger; Boris Landa (CoRR, 2025)