World model as a graph: Learning latent landmarks for planning L Zhang, G Yang, BC Stadie International conference on machine learning, 12611-12620, 2021 | 77 | 2021 |
Learning unsupervised world models for autonomous driving via discrete diffusion L Zhang, Y Xiong, Z Yang, S Casas, R Hu, R Urtasun International Conference on Learning Representations (ICLR); arXiv preprint …, 2023 | 25 | 2023 |
Towards unsupervised object detection from lidar point clouds L Zhang, AJ Yang, Y Xiong, S Casas, B Yang, M Ren, R Urtasun Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 24 | 2023 |
Learning Intrinsic Rewards as a Bi-Level Optimization Problem B Stadie, L Zhang, J Ba Conference on Uncertainty in Artificial Intelligence, 111-120, 2020 | 23 | 2020 |
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, 2023 | 7 | 2023 |
Generative Verifiers: Reward Modeling as Next-Token Prediction L Zhang, A Hosseini, H Bansal, M Kazemi, A Kumar, R Agarwal arXiv preprint arXiv:2408.15240, 2024 | 1 | 2024 |
World Model as a Graph: Learning Latent Landmarks for Planning Supplementary Materials L Zhang, G Yang, B Stadie | | |