| Estimating information flow in deep neural networks Z Goldfeld, E Berg, K Greenewald, I Melnyk, N Nguyen, B Kingsbury, ... arXiv preprint arXiv:1810.05728, 2018 | 176 | 2018 |
| The information bottleneck problem and its applications in machine learning Z Goldfeld, Y Polyanskiy IEEE Journal on Selected Areas in Information Theory 1 (1), 19-38, 2020 | 156 | 2020 |
| Convergence of smoothed empirical measures with applications to entropy estimation Z Goldfeld, K Greenewald, J Niles-Weed, Y Polyanskiy arXiv preprint arXiv:1905.13576, 2019 | 86* | 2019 |
| Semantic-security capacity for wiretap channels of type II Z Goldfeld, P Cuff, HH Permuter IEEE Transactions on Information Theory 62 (7), 3863-3879, 2016 | 75 | 2016 |
| Sliced mutual information: A scalable measure of statistical dependence Z Goldfeld, K Greenewald Advances in Neural Information Processing Systems 34, 17567-17578, 2021 | 50 | 2021 |
| Statistical inference with regularized optimal transport Z Goldfeld, K Kato, G Rioux, R Sadhu Information and Inference: A Journal of the IMA 13 (1), iaad056, 2024 | 46 | 2024 |
| Statistical, robustness, and computational guarantees for sliced wasserstein distances S Nietert, Z Goldfeld, R Sadhu, K Kato Advances in Neural Information Processing Systems 35, 28179-28193, 2022 | 45 | 2022 |
| Arbitrarily varying wiretap channels with type constrained states Z Goldfeld, P Cuff, HH Permuter IEEE Transactions on Information Theory 62 (12), 7216-7244, 2016 | 43 | 2016 |
| Neural estimation of statistical divergences S Sreekumar, Z Goldfeld Journal of machine learning research 23 (126), 1-75, 2022 | 42 | 2022 |
| Gaussian-smoothed optimal transport: Metric structure and statistical efficiency Z Goldfeld, K Greenewald International Conference on Artificial Intelligence and Statistics, 3327-3337, 2020 | 39 | 2020 |
| Limit theorems for entropic optimal transport maps and Sinkhorn divergence Z Goldfeld, K Kato, G Rioux, R Sadhu Electronic Journal of Statistics 18 (1), 980-1041, 2024 | 38 | 2024 |
| Outlier-robust optimal transport: Duality, structure, and statistical analysis S Nietert, Z Goldfeld, R Cummings International Conference on Artificial Intelligence and Statistics, 11691-11719, 2022 | 35 | 2022 |
| Smooth -Wasserstein Distance: Structure, Empirical Approximation, and Statistical Applications S Nietert, Z Goldfeld, K Kato International Conference on Machine Learning, 8172-8183, 2021 | 35 | 2021 |
| Wiretap channels with random states non-causally available at the encoder Z Goldfeld, P Cuff, HH Permuter IEEE Transactions on Information Theory 66 (3), 1497-1519, 2019 | 35 | 2019 |
| Fourier-Motzkin Elimination Software for Information Theoretic Inequalities IB Gattegno, Z Goldfeld, HH Permuter arXiv preprint arXiv:1610.03990, 2016 | 30 | 2016 |
| Asymptotic guarantees for generative modeling based on the smooth Wasserstein distance Z Goldfeld, K Greenewald, K Kato Advances in neural information processing systems 33, 2527-2539, 2020 | 26* | 2020 |
| Estimating information flow in neural networks Z Goldfeld, E van den Berg, K Greenewald, I Melnyk, N Nguyen, ... arXiv preprint arXiv:1810.05728, 2018 | 26 | 2018 |
| Neural estimation and optimization of directed information over continuous spaces D Tsur, Z Aharoni, Z Goldfeld, H Permuter IEEE Transactions on Information Theory 69 (8), 4777-4798, 2023 | 24 | 2023 |
| Capacity of continuous channels with memory via directed information neural estimator Z Aharoni, D Tsur, Z Goldfeld, HH Permuter 2020 IEEE International Symposium on Information Theory (ISIT), 2014-2019, 2020 | 24 | 2020 |
| Non-asymptotic performance guarantees for neural estimation of f-divergences S Sreekumar, Z Zhang, Z Goldfeld International Conference on Artificial Intelligence and Statistics, 3322-3330, 2021 | 22 | 2021 |
Haim H. PermuterBen Gurion UniversityVerified email at bgu.ac.il
