Privacy-preserving and Uncertainty-aware Federated Trajectory Prediction
for Connected Autonomous Vehicles

Privacy-preserving and Uncertainty-aware Federated Trajectory Prediction for Connected Autonomous Vehicles

IEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2023

8 March 2023

Lili Su

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Papers citing "Privacy-preserving and Uncertainty-aware Federated Trajectory Prediction for Connected Autonomous Vehicles"

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Title
DroneFL: Federated Learning for Multi-UAV Visual Target Tracking Xiaofan Yu Yuwei Wu Katherine Mao Ye Tian Vijay Kumar Tajana Rosing FedML 116 1 0 25 Sep 2025
Efficient Federated Learning against Heterogeneous and Non-stationary Client UnavailabilityNeural Information Processing Systems (NeurIPS), 2024 Ming Xiang Stratis Ioannidis Edmund Yeh Carlee Joe-Wong Lili Su FedML 307 9 0 26 Sep 2024
Building Real-time Awareness of Out-of-distribution in Trajectory Prediction for Autonomous Vehicles Tongfei Guo Rui Liu Lili Su 291 4 0 25 Sep 2024
On the Convergence Rates of Federated Q-Learning across Heterogeneous Environments Muxing Wang Pengkun Yang Lili Su FedML 355 2 0 05 Sep 2024
Fast and Robust State Estimation and Tracking via Hierarchical LearningIEEE Transactions on Automatic Control (TAC), 2023 Connor Mclaughlin Matthew Ding Deniz Edogmus Lili Su 174 0 0 29 Jun 2023