Learning to Reweight Examples for Robust Deep Learning M Ren, W Zeng, B Yang, R Urtasun ICML 2018, 2018 | 1609 | 2018 |
End-To-End Interpretable Neural Motion Planner W Zeng, W Luo, S Suo, A Sadat, B Yang, S Casas, R Urtasun CVPR 2019, 2019 | 422 | 2019 |
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 | 297 | 2020 |
LiDARsim: Realistic LiDAR Simulation by Leveraging the Real World S Manivasagam, S Wang, K Wong, W Zeng, M Sazanovich, S Tan, ... CVPR 2020, 2020 | 211 | 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 | 173 | 2020 |
LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting W Zeng, M Liang, R Liao, R Urtasun IROS 2021, 2021 | 157 | 2021 |
Efficient summarization with read-again and copy mechanism W Zeng, W Luo, S Fidler, R Urtasun arXiv preprint arXiv:1611.03382, 2016 | 125 | 2016 |
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 | 121 | 2020 |
Incorporating relation paths in neural relation extraction W Zeng, Y Lin, Z Liu, M Sun EMNLP 2017, 2016 | 101 | 2016 |
Dsdnet: Deep structured self-driving network W Zeng, S Wang, R Liao, Y Chen, B Yang, R Urtasun ECCV 2020, 2020 | 98 | 2020 |
Differentiable Compositional Kernel Learning for Gaussian Processes S Sun, G Zhang, C Wang, W Zeng, J Li, R Grosse ICML 2018, 2018 | 89 | 2018 |
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 | 59 | 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 | 54 | 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 | 53 | 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 | 46 | 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 | 44 | 2020 |
Self-Supervised Representation Learning from Flow Equivariance Y Xiong, M Ren, W Zeng, R Urtasun ICCV 2021, 2021 | 37 | 2021 |
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 | 36 | 2020 |
Deep Structured Reactive Planning J Liu, W Zeng, R Urtasun, E Yumer ICRA 2021, 2021 | 28 | 2021 |
MLPrune: Multi-Layer Pruning for Automated Neural Network Compression W Zeng, R Urtasun | 28* | 2018 |