| On the exact Berk-Jones statistics and their -value calculation A Moscovich, B Nadler, C Spiegelman Electronic Journal of Statistics 10 (2), 2329-2354, 2016 | 68 | 2016 |
| Cryo-EM reconstruction of continuous heterogeneity by Laplacian spectral volumes A Moscovich, A Halevi, J Andén, A Singer Inverse Problems 36 (2), 024003, 2020 | 59 | 2020 |
| Minimax-optimal semi-supervised regression on unknown manifolds A Moscovich, A Jaffe, B Nadler Proceedings of the 20th International Conference on Artificial Intelligence …, 2017 | 39 | 2017 |
| Manifold learning with arbitrary norms J Kileel, A Moscovich, N Zelesko, A Singer Journal of Fourier Analysis and Applications 27 (5), 1-56, 2021 | 28 | 2021 |
| Fast calculation of boundary crossing probabilities for Poisson processes A Moscovich, B Nadler Statistics & Probability Letters 123, 177-182, 2017 | 27 | 2017 |
| Earthmover-based manifold learning for analyzing molecular conformation spaces N Zelesko, A Moscovich, J Kileel, A Singer 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 1715-1719, 2020 | 24 | 2020 |
| Unsupervised particle sorting for high-resolution single-particle cryo-EM Y Zhou, A Moscovich, T Bendory, A Bartesaghi Inverse Problems 36 (4), 044002, 2020 | 23 | 2020 |
| Product manifold learning S Zhang, A Moscovich, A Singer International Conference on Artificial Intelligence and Statistics, 3241-3249, 2021 | 17 | 2021 |
| On the cross-validation bias due to unsupervised pre-processing A Moscovich, S Rosset Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2022 | 16 | 2022 |
| The Calibrated Kolmogorov-Smirnov Test A Moscovich-Eiger, B Nadler, C Spiegelman arXiv preprint arXiv:1311.3190v3, 2014 | 16* | 2014 |
| Wasserstein k-means for clustering tomographic projections R Rao, A Moscovich, A Singer Machine Learning for Structural Biology workshop, Neural Information …, 2020 | 15 | 2020 |
| Fast calculation of p-values for one-sided Kolmogorov-Smirnov type statistics A Moscovich Computational Statistics & Data Analysis 185, 107769, 2023 | 11 | 2023 |
| Data-driven determination of number of discrete conformations in single-particle cryo-EM Y Zhou, A Moscovich, A Bartesaghi Computer methods and programs in biomedicine 221, 106892, 2022 | 9 | 2022 |
| Hidden Markov modeling of single-particle diffusion with stochastic tethering A Federbush, A Moscovich, Y Bar-Sinai Physical Review E 109 (3), 034129, 2024 | 1 | 2024 |
| Spectral extraction of unique latent variables S Yoffe, A Moscovich, A Jaffe arXiv e-prints, arXiv: 2402.18741, 2024 | 1 | 2024 |
| Beyond trees: Classification with sparse pairwise dependencies Y Tenzer, A Moscovich, MF Dorn, B Nadler, C Spiegelman Journal of machine learning research 21 (189), 1-33, 2020 | 1 | 2020 |
| Spectral Extraction of Distinctive Latent Variables S Yoffe, A Moscovich, A Jaffe arXiv preprint arXiv:2402.18741, 2024 | | 2024 |
| Fast computation of boundary crossing probabilities for the empirical CDF (poster) A Moscovich-Eiger, B Nadler http://www.wisdom.weizmann.ac.il/~amitmo/crossprob …, 2015 | | 2015 |
| Tail-sensitive goodness-of-fit (poster) A Moscovich-Eiger, B Nadler, C Spiegelman | | 2014 |
| Fast semi-supervised regression: a geodesic nearest neighbor approach A Moscovich, A Jaffe, B Nadler | | |
Boaz NadlerWeizmann Institute of Science, IsraelВерификована је имејл адреса на weizmann.ac.il