| Provably Safe Robot Navigation with Obstacle Uncertainty B Axelrod, LP Kaelbling, T Lozano-Pérez Robotics Science and Systems 13, 2017 | 80 | 2017 |
| Causal strategic linear regression Y Shavit, B Edelman, B Axelrod International Conference on Machine Learning, 8676-8686, 2020 | 77 | 2020 |
| Near-optimal approximate discrete and continuous submodular function minimization B Axelrod, YP Liu, A Sidford Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete …, 2020 | 27 | 2020 |
| Sample amplification: Increasing dataset size even when learning is impossible B Axelrod, S Garg, V Sharan, G Valiant International Conference on Machine Learning, 442-451, 2020 | 16 | 2020 |
| Learning from strategic agents: Accuracy, improvement, and causality Y Shavit, B Edelman, B Axelrod arXiv preprint arXiv:2002.10066, 2020 | 14 | 2020 |
| Hardness of 3d motion planning under obstacle uncertainty L Shimanuki, B Axelrod International Workshop on the Algorithmic Foundations of Robotics, 852-867, 2018 | 14 | 2018 |
| A polynomial time algorithm for log-concave maximum likelihood via locally exponential families B Axelrod, I Diakonikolas, A Stewart, A Sidiropoulos, G Valiant Advances in Neural Information Processing Systems 32, 2019 | 12 | 2019 |
| USE-Evaluator: Performance metrics for medical image segmentation models supervised by uncertain, small or empty reference annotations in neuroimaging S Ostmeier, B Axelrod, F Isensee, J Bertels, M Mlynash, S Christensen, ... Medical Image Analysis 90, 102927, 2023 | 8 | 2023 |
| Hardness of motion planning with obstacle uncertainty in two dimensions L Shimanuki, B Axelrod The International Journal of Robotics Research 40 (10-11), 1151-1166, 2021 | 8 | 2021 |
| Algorithms for safe robot navigation BM Axelrod Massachusetts Institute of Technology, 2017 | 6 | 2017 |
| Random expert sampling for deep learning segmentation of acute ischemic stroke on non-contrast CT S Ostmeier, B Axelrod, Y Liu, Y Yu, B Jiang, N Yuen, B Pulli, ... Journal of NeuroInterventional Surgery, 2024 | 4 | 2024 |
| On the statistical complexity of sample amplification B Axelrod, S Garg, Y Han, V Sharan, G Valiant arXiv preprint arXiv:2201.04315, 2022 | 4 | 2022 |
| An efficient algorithm for high-dimensional log-concave maximum likelihood B Axelrod, G Valiant arXiv preprint arXiv:1811.03204, 2018 | 4 | 2018 |
| Reducing FPGA algorithm area by avoiding redundant computation B Axelrod, M Laverne 2015 IEEE International Conference on Robotics and Automation (ICRA), 503-508, 2015 | 3 | 2015 |
| Non-inferiority of deep learning ischemic stroke segmentation on non-contrast CT within 16-hours compared to expert neuroradiologists S Ostmeier, B Axelrod, BFJ Verhaaren, S Christensen, A Mahammedi, ... Scientific Reports 13 (1), 16153, 2023 | 2 | 2023 |
| Non-inferiority of Deep Learning Acute Ischemic Stroke Segmentation on Non-Contrast CT Compared to Expert Neuroradiologists S Ostmeier, B Axelrod, BFJ Verhaaren, S Christensen, A Mahammedi, ... arXiv preprint arXiv:2211.15341, 2022 | 2 | 2022 |
| LieRE: Generalizing Rotary Position Encodings S Ostmeier, B Axelrod, ME Moseley, A Chaudhari, C Langlotz arXiv preprint arXiv:2406.10322, 2024 | 1 | 2024 |
| Efficient Motion Planning Under Obstacle Uncertainty with Local Dependencies B Axelrod, L Shimanuki International Workshop on the Algorithmic Foundations of Robotics, 68-84, 2022 | | 2022 |
| Sidestepping Hardness in Statistical Problems B Axelrod Stanford University, 2022 | | 2022 |
| Sample Amplification: Increasing Dataset Size even when Learning is Impossible, ICML B Axelrod, S Garg, V Sharan, V Gregory Proceedings of Machine Learning Research, 2020 | | 2020 |
Benjamin L. EdelmanHarvard UniversityVerified email at g.harvard.edu
