| V2vnet: Vehicle-to-vehicle communication for joint perception and prediction TH Wang, S Manivasagam, M Liang, B Yang, W Zeng, R Urtasun Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 337 | 2020 |
| Physically realizable adversarial examples for lidar object detection J Tu, M Ren, S Manivasagam, M Liang, B Yang, R Du, F Cheng, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 233 | 2020 |
| Advsim: Generating safety-critical scenarios for self-driving vehicles J Wang, A Pun, J Tu, S Manivasagam, A Sadat, S Casas, M Ren, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 152 | 2021 |
| Spear: Optimized dependency-aware task scheduling with deep reinforcement learning Z Hu, J Tu, B Li 2019 IEEE 39th international conference on distributed computing systems …, 2019 | 82 | 2019 |
| Exploring adversarial robustness of multi-sensor perception systems in self driving J Tu, H Li, X Yan, M Ren, Y Chen, M Liang, E Bitar, E Yumer, R Urtasun arXiv preprint arXiv:2101.06784, 2021 | 77 | 2021 |
| Learning to communicate and correct pose errors N Vadivelu, M Ren, J Tu, J Wang, R Urtasun Conference on Robot Learning, 1195-1210, 2021 | 52 | 2021 |
| Adversarial Attacks On Multi-Agent Communication J Tu, T Wang, J Wang, S Manivasagam, M Ren, R Urtasun ICCV 2021, 2021 | 52 | 2021 |
| Mixsim: A hierarchical framework for mixed reality traffic simulation S Suo, K Wong, J Xu, J Tu, A Cui, S Casas, R Urtasun Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 25 | 2023 |
| Strobe: Streaming object detection from lidar packets D Frossard, S Suo, S Casas, J Tu, R Hu, R Urtasun CORL 2020, 2020 | 16 | 2020 |
| Diverse Complexity Measures for Dataset Curation in Self-driving A Sadat, S Segal, S Casas, J Tu, B Yang, R Urtasun, E Yumer IROS 2021, 2021 | 11 | 2021 |
| Learning realistic traffic agents in closed-loop C Zhang, J Tu, L Zhang, K Wong, S Suo, R Urtasun arXiv preprint arXiv:2311.01394, 2023 | 10 | 2023 |
| Systems and methods for training object detection models using adversarial examples X Tu, S Manivasagam, M Ren, M Liang, B Yang, R Urtasun US Patent 11,686,848, 2023 | 8 | 2023 |
| Adv3d: Generating safety-critical 3d objects through closed-loop simulation J Sarva, J Wang, J Tu, Y Xiong, S Manivasagam, R Urtasun arXiv preprint arXiv:2311.01446, 2023 | 4 | 2023 |
| Towards Scalable Coverage-Based Testing of Autonomous Vehicles J Tu, S Suo, C Zhang, K Wong, R Urtasun Conference on Robot Learning, 2611-2623, 2023 | 1 | 2023 |
| Validation for autonomous systems J Tu, SUO Simon, R Urtasun US Patent App. 18/598,789, 2024 | | 2024 |
| Imitation and reinforcement learning for multi-agent simulation C Zhang, J Tu, L Zhang, K Wong, SUO Simon, R Urtasun US Patent App. 18/598,975, 2024 | | 2024 |
| 3D Reasoning for Unsupervised Anomaly Detection in Pediatric WbMRI A Chang, V Suriyakumar, A Moturu, J Tu, N Tewattanarat, S Joshi, A Doria, ... arXiv preprint arXiv:2103.13497, 2021 | | 2021 |
| Learning Realistic Traffic Agents in Closed-loop C Zhang, J Tu, L Zhang, K Wong, S Suo, R Urtasun 7th Annual Conference on Robot Learning, 0 | | |
| Supplementary Material-STROBE: Streaming Object Detection from LiDAR Packets D Frossard, S Suo, S Casas, J Tu, R Hu, R Urtasun | | |
| The Feminine Mystique: Women & Gaming T Olson, J Tu | | |
