The power of depth for feedforward neural networks R Eldan, O Shamir Conference on learning theory, 907-940, 2016 | 558 | 2016 |

Kernel-based methods for bandit convex optimization S Bubeck, YT Lee, R Eldan Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing …, 2017 | 104 | 2017 |

Sampling from a log-concave distribution with projected langevin monte carlo S Bubeck, R Eldan, J Lehec Discrete & Computational Geometry 59 (4), 757-783, 2018 | 83 | 2018 |

Thin shell implies spectral gap up to polylog via a stochastic localization scheme R Eldan Geometric and Functional Analysis 23 (2), 532-569, 2013 | 81 | 2013 |

Testing for high‐dimensional geometry in random graphs S Bubeck, J Ding, R Eldan, MZ Rácz Random Structures & Algorithms 49 (3), 503-532, 2016 | 75 | 2016 |

A two-sided estimate for the Gaussian noise stability deficit R Eldan Inventiones mathematicae 201 (2), 561-624, 2015 | 66 | 2015 |

Multi-scale exploration of convex functions and bandit convex optimization S Bubeck, R Eldan Conference on Learning Theory, 583-589, 2016 | 63 | 2016 |

Approximately gaussian marginals and the hyperplane conjecture R Eldan, B Klartag Concentration, functional inequalities and isoperimetry 545, 55-68, 2011 | 55 | 2011 |

Gaussian-width gradient complexity, reverse log-Sobolev inequalities and nonlinear large deviations R Eldan Geometric and Functional Analysis 28 (6), 1548-1596, 2018 | 54 | 2018 |

The entropic barrier: a simple and optimal universal self-concordant barrier S Bubeck, R Eldan arXiv preprint arXiv:1412.1587, 2014 | 42 | 2014 |

Pointwise estimates for marginals of convex bodies R Eldan, B Klartag Journal of Functional Analysis 254 (8), 2275-2293, 2008 | 36 | 2008 |

Volumetric properties of the convex hull of an -dimensional Brownian motion R Eldan Electronic Journal of Probability 19, 1-34, 2014 | 34 | 2014 |

Finite-time analysis of projected Langevin Monte Carlo S Bubeck, R Eldan, J Lehec Advances in Neural Information Processing Systems, 1243-1251, 2015 | 30 | 2015 |

Bandit Smooth Convex Optimization: Improving the Bias-Variance Tradeoff. O Dekel, R Eldan, T Koren NIPS, 2926-2934, 2015 | 29 | 2015 |

From trees to seeds: on the inference of the seed from large trees in the uniform attachment model S Bubeck, R Eldan, E Mossel, MZ Rácz Bernoulli 23 (4A), 2887-2916, 2017 | 25 | 2017 |

Dimensionality and the stability of the Brunn-Minkowski inequality R Eldan, B Klartag arXiv preprint arXiv:1110.6584, 2011 | 24 | 2011 |

The CLT in high dimensions: quantitative bounds via martingale embedding R Eldan, D Mikulincer, A Zhai The Annals of Probability 48 (5), 2494-2524, 2020 | 20 | 2020 |

On multiple peaks and moderate deviations for the supremum of a Gaussian field J Ding, R Eldan, A Zhai The Annals of Probability 43 (6), 3468-3493, 2015 | 19 | 2015 |

Decomposition of mean-field Gibbs distributions into product measures R Eldan, R Gross Electronic Journal of Probability 23, 1-24, 2018 | 15 | 2018 |

Stability of the logarithmic Sobolev inequality via the Föllmer process R Eldan, J Lehec, Y Shenfeld Annales de l'Institut Henri Poincaré, Probabilités et Statistiques 56 (3 …, 2020 | 14 | 2020 |