| Learning to Reweight Examples for Robust Deep Learning M Ren, W Zeng, B Yang, R Urtasun ICML 2018, 2018 | 1973 | 2018 |
| V2vnet: Vehicle-to-vehicle communication for joint perception and prediction TH Wang, S Manivasagam, M Liang, B Yang, W Zeng, R Urtasun ECCV 2020, 2020 | 658 | 2020 |
| End-To-End Interpretable Neural Motion Planner W Zeng, W Luo, S Suo, A Sadat, B Yang, S Casas, R Urtasun CVPR 2019, 2019 | 583 | 2019 |
| LiDARsim: Realistic LiDAR Simulation by Leveraging the Real World S Manivasagam, S Wang, K Wong, W Zeng, M Sazanovich, S Tan, ... CVPR 2020, 2020 | 343 | 2020 |
| PnPNet: End-to-End Perception and Prediction with Tracking in the Loop M Liang, B Yang, W Zeng, Y Chen, R Hu, S Casas, R Urtasun CVPR 2020, 2020 | 260 | 2020 |
| LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting W Zeng, M Liang, R Liao, R Urtasun IROS 2021, 2021 | 258 | 2021 |
| End-to-end Contextual Perception and Prediction with Interaction Transformer LL Li, B Yang, M Liang, W Zeng, M Ren, S Segal, R Urtasun IROS 2020, 2020 | 161 | 2020 |
| Efficient summarization with read-again and copy mechanism W Zeng, W Luo, S Fidler, R Urtasun arXiv preprint arXiv:1611.03382, 2016 | 137 | 2016 |
| Dsdnet: Deep structured self-driving network W Zeng, S Wang, R Liao, Y Chen, B Yang, R Urtasun ECCV 2020, 2020 | 133 | 2020 |
| Differentiable Compositional Kernel Learning for Gaussian Processes S Sun, G Zhang, C Wang, W Zeng, J Li, R Grosse ICML 2018, 2018 | 109 | 2018 |
| Incorporating relation paths in neural relation extraction W Zeng, Y Lin, Z Liu, M Sun EMNLP 2017, 2016 | 106 | 2016 |
| Systems and methods for generating synthetic sensor data via machine learning S Manivasagam, S Wang, WC Ma, KKW Wong, W Zeng, R Urtasun US Patent 11,544,167, 2023 | 93 | 2023 |
| End-to-end interpretable motion planner for autonomous vehicles W Zeng, W Luo, A Sadat, B Yang, R Urtasun US Patent 11,755,018, 2023 | 82 | 2023 |
| Weakly-supervised 3D Shape Completion in the Wild J Gu, WC Ma, S Manivasagam, W Zeng, Z Wang, Y Xiong, H Su, ... ECCV 2020, 2020 | 72 | 2020 |
| Auto4d: Learning to label 4d objects from sequential point clouds B Yang, M Bai, M Liang, W Zeng, R Urtasun arXiv preprint arXiv:2101.06586, 2021 | 66 | 2021 |
| Perceive, Attend, and Drive: Learning Spatial Attention for Safe Self-Driving B Wei, M Ren, W Zeng, M Liang, B Yang, R Urtasun ICRA 2021, 2020 | 54 | 2020 |
| Permute, Quantize, and Fine-tune: Efficient Compression of Neural Networks J Martinez, J Shewakramani, TW Liu, IA Bârsan, W Zeng, R Urtasun CVPR 2021, 2020 | 54 | 2020 |
| Self-Supervised Representation Learning from Flow Equivariance Y Xiong, M Ren, W Zeng, R Urtasun ICCV 2021, 2021 | 51 | 2021 |
| Rethinking closed-loop training for autonomous driving C Zhang, R Guo, W Zeng, Y Xiong, B Dai, R Hu, M Ren, R Urtasun ECCV, 264-282, 2022 | 46 | 2022 |
| Deep Structured Reactive Planning J Liu, W Zeng, R Urtasun, E Yumer ICRA 2021, 2021 | 35 | 2021 |
Raquel UrtasunFounder & CEO Waabi, Professor, University of Toronto.Verified email at cs.toronto.edu
