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Predicting the motion of dynamic agents is a critical task for guaranteeing the safety of autonomous systems.
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M. Liang, B. Yang, R. Hu, Y. Chen, R. Liao, S. Feng, and R. Urtasun, “Learning Lane Graph Representations for Motion Forecasting,” in Computer Vision – ECCV 2020 , ser. Lecture Notes in Computer Science, A. Vedaldi, H. Bischof, T. Brox, and J.-M. Frahm, Eds. Cham: Springer International Publishing, 2020, pp. 541–556
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F. Djeumou, C. Neary, E. Goubault, S. Putot, and U. Topcu, “Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling,” in Proceedings of The 4th Annual Learning for Dynamics and Control Conference . PMLR, May 2022, pp. 263–277, iSSN: 2640-3498. [Online]. Available: https://proceedings.mlr.press/v168/djeumou22a.html
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P. Karle, M. Geisslinger, J. Betz, and M. Lienkamp, “Scenario Understanding and Motion Prediction for Autonomous Vehicles - Review and Comparison,” IEEE Transactions on Intelligent Transportation Systems , pp. 1–21, 2022, conference Name: IEEE Transactions on Intelligent Transportation Systems
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M. O’Kelly, H. Zheng, D. Karthik, and R. Mangharam, “F1TENTH: An Open-source Evaluation Environment for Continuous Control and Reinforcement Learning,” in Proceedings of the NeurIPS 2019 Competition and Demonstration Track . PMLR, Aug. 2020, pp. 77–89, iSSN: 2640-3498. [Online]. Available: https://proceedings.mlr.press/v123/o-kelly20a.html
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2021
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K. Stankeviciute, A. M. Alaa, and M. van der Schaar, “Conformal Time-series Forecasting,” in Advances in Neural Information Processing Systems , vol. 34. Curran Associates, Inc., 2021, pp. 6216–6228. [Online]. Available: https://proceedings.neurips.cc/paper/2021/hash/312f1ba2a72318edaaa995a67835fad5-Abstract.html
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Q. Zhang, S. Hu, J. Sun, Q. A. Chen, and Z. M. Mao, “On Adversarial Robustness of Trajectory Prediction for Autonomous Vehicles,” in 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , Jun. 2022, pp. 15 138–15 147, iSSN: 2575-7075
2022
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B. Varadarajan, A. Hefny, A. Srivastava, K. S. Refaat, N. Nayakanti, A. Cornman, K. Chen, B. Douillard, C. P. Lam, D. Anguelov, and B. Sapp, “MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior Prediction,” in 2022 International Conference on Robotics and Automation (ICRA) , May 2022, pp. 7814–7821
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2022
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2022
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2022
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