| Hierarchical Shrinkage: Improving the accuracy and interpretability of tree-based models. A Agarwal, YS Tan, O Ronen, C Singh, B Yu International Conference on Machine Learning, 111-135, 2022 | 42 | 2022 |
| Fast interpretable greedy-tree sums (FIGS) Y Shuo Tan, C Singh, K Nasseri, A Agarwal, J Duncan, O Ronen, ... arXiv preprint arXiv:2201.11931, 2022 | 29* | 2022 |
| Learning epistatic polygenic phenotypes with Boolean interactions M Behr, K Kumbier, A Cordova-Palomera, M Aguirre, O Ronen, C Ye, ... Plos one 19 (4), e0298906, 2024 | 7 | 2024 |
| A mixing time lower bound for a simplified version of BART O Ronen, T Saarinen, YS Tan, J Duncan, B Yu arXiv preprint arXiv:2210.09352, 2022 | 5 | 2022 |
| Epistasis regulates genetic control of cardiac hypertrophy Q Wang, TM Tang, N Youlton, CS Weldy, AM Kenney, O Ronen, ... Research Square, 2023 | 1 | 2023 |
| The Computational Curse of Big Data for Bayesian Additive Regression Trees: A Hitting Time Analysis YS Tan, O Ronen, T Saarinen, B Yu arXiv preprint arXiv:2406.19958, 2024 | | 2024 |
| ScaLES: Scalable Latent Exploration Score for Pre-Trained Generative Networks O Ronen, AI Humayun, R Balestriero, R Baraniuk, B Yu arXiv preprint arXiv:2406.09657, 2024 | | 2024 |
| Deep Homology-Based Protein Contact-Map Prediction O Ronen, O Zuk bioRxiv, 2020.10. 04.325274, 2020 | | 2020 |
