| Lecture notes in high dimensional statistics P Rigollet, JC Hütter Zentralblatt MATH 1372, 2015 | 264* | 2015 |
| Cycling cancer persister cells arise from lineages with distinct programs Y Oren, M Tsabar, MS Cuoco, L Amir-Zilberstein, HF Cabanos, JC Hütter, ... Nature 596 (7873), 576-582, 2021 | 255 | 2021 |
| Skin-resident innate lymphoid cells converge on a pathogenic effector state P Bielecki, SJ Riesenfeld, JC Hütter, E Torlai Triglia, MS Kowalczyk, ... Nature, 1-5, 2021 | 127 | 2021 |
| Optimal rates for total variation denoising JC Hütter, P Rigollet Conference on Learning Theory, 1115-1146, 2016 | 102 | 2016 |
| Minimax estimation of smooth optimal transport maps JC Hütter, P Rigollet | 99 | 2021 |
| Statistical optimal transport via factored couplings A Forrow, JC Hütter, M Nitzan, P Rigollet, G Schiebinger, J Weed The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 72 | 2019 |
| Stepwise-edited, human melanoma models reveal mutations’ effect on tumor and microenvironment E Hodis, ET Triglia, JYH Kwon, T Biancalani, LR Zakka, S Parkar, ... Science 376 (6592), eabi8175, 2022 | 25 | 2022 |
| Large-scale differentiable causal discovery of factor graphs R Lopez, JC Hütter, J Pritchard, A Regev Advances in Neural Information Processing Systems 35, 19290-19303, 2022 | 22 | 2022 |
| Estimation of Monge matrices JC Hütter, C Mao, P Rigollet, E Robeva | 10 | 2020 |
| Disentangling shared and group-specific variations in single-cell transcriptomics data with multiGroupVI E Weinberger, R Lopez, JC Hütter, A Regev Machine Learning in Computational Biology, 16-32, 2022 | 9 | 2022 |
| Biological cartography: Building and benchmarking representations of life S Celik, JC Hütter, SM Carlos, NH Lazar, R Mohan, C Tillinghast, ... Biorxiv, 2022.12. 09.519400, 2022 | 9 | 2022 |
| Nodags-flow: Nonlinear cyclic causal structure learning MG Sethuraman, R Lopez, R Mohan, F Fekri, T Biancalani, JC Hütter International Conference on Artificial Intelligence and Statistics, 6371-6387, 2023 | 8 | 2023 |
| Consistency of probability measure quantization by means of power repulsion–attraction potentials M Fornasier, JC Hütter Journal of Fourier Analysis and Applications 22 (3), 694-749, 2016 | 8 | 2016 |
| Maximum likelihood estimation for brownian motion tree models based on one sample M Truell, JC Hütter, C Squires, P Zwiernik, C Uhler arXiv preprint arXiv:2112.00816, 2021 | 7 | 2021 |
| Optimal rates for estimation of two-dimensional totally positive distributions JC Hütter, C Mao, P Rigollet, E Robeva | 3 | 2020 |
| Estimation rates for sparse linear cyclic causal models JC Huetter, P Rigollet Conference on Uncertainty in Artificial Intelligence, 1169-1178, 2020 | 2 | 2020 |
| Minimax estimation with structured data: Shape constraints, causal models, and optimal transport JCK Hütter Massachusetts Institute of Technology, 2019 | 2 | 2019 |
| A Supervised Contrastive Framework for Learning Disentangled Representations of Cellular Perturbation Data X Tu, JC Hütter, ZJ Wang, T Kudo, A Regev, R Lopez Machine Learning in Computational Biology, 90-100, 2024 | 1 | 2024 |
| Supplement to “Estimation of Monge Matrices.” JC Hütter, C Mao, P Rigollet, E Robeva | 1 | 2020 |
| Asymptotic Behavior of Gradient Flows Driven by Nonlocal Power Repulsion and Attraction Potentials in One Dimension M Di Francesco, M Fornasier, JC Hütter, D Matthes SIAM Journal on Mathematical Analysis 46 (6), 3814-3837, 2014 | 1 | 2014 |
