Peide Huang

According to our database, Peide Huang authored at least 18 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

CaDRE: Controllable and Diverse Generation of Safety-Critical Driving Scenarios using Real-World Trajectories.

Peide Huang, Wenhao Ding, Jonathan Francis, Bingqing Chen, Ding Zhao

CoRR, 2024

Construction of Virtual Simulation Teaching Platform for Risk Experimental Projects in VR Environment.

Gaocai Fu, Yu Jiang, Jun Xiao, Peide Huang, Xu Luo, Minhui Ni, Xianjv Liu

Proceedings of the 2024 7th International Conference on Software Engineering and Information Management, 2024

2023

Gradient Shaping for Multi-Constraint Safe Reinforcement Learning.

Yihang Yao, Zuxin Liu, Zhepeng Cen, Peide Huang, Tingnan Zhang, Wenhao Yu, Ding Zhao

CoRR, 2023

Creative Robot Tool Use with Large Language Models.

Mengdi Xu, Peide Huang, Wenhao Yu, Shiqi Liu, Xilun Zhang, Yaru Niu, Tingnan Zhang, Fei Xia, Jie Tan, Ding Zhao

CoRR, 2023

Multimodal Representation Learning of Cardiovascular Magnetic Resonance Imaging.

Jielin Qiu, Peide Huang, Makiya Nakashima, Jaehyun Lee, Jiacheng Zhu, W. H. Wilson Tang, Pohao Chen, Christopher Nguyen, Byung-Hak Kim, Debbie Kwon, Douglas Weber, Ding Zhao, David Chen

CoRR, 2023

GameVibes: Vibration-based Crowd Monitoring for Sports Games through Audience-Game-Facility Association Modeling.

Yiwen Dong, Yuyan Wu, Jesse R. Codling, Jatin Aggarwal, Peide Huang, Wenhao Ding, Hugo Latapie, Pei Zhang, Hae Young Noh

Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, 2023

Characterizing Crowd Preferences on Stadium Facilities through Dynamic Inverse Reinforcement Learning.

Yiwen Dong, Peide Huang, Hae Young Noh

Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, 2023

Cardiac Disease Diagnosis on Imbalanced Electrocardiography Data Through Optimal Transport Augmentation.

Jielin Qiu, Jiacheng Zhu, Mengdi Xu, Peide Huang, Michael A. Rosenberg, Douglas Weber, Emerson Liu, Ding Zhao

Proceedings of the IEEE International Conference on Acoustics, 2023

Continual Vision-based Reinforcement Learning with Group Symmetries.

Shiqi Liu, Mengdi Xu, Peide Huang, Xilun Zhang, Yongkang Liu, Kentaro Oguchi, Ding Zhao

Proceedings of the Conference on Robot Learning, 2023

What Went Wrong? Closing the Sim-to-Real Gap via Differentiable Causal Discovery.

Peide Huang, Xilun Zhang, Ziang Cao, Shiqi Liu, Mengdi Xu, Wenhao Ding, Jonathan Francis, Bingqing Chen, Ding Zhao

Proceedings of the Conference on Robot Learning, 2023

Group Distributionally Robust Reinforcement Learning with Hierarchical Latent Variables.

Mengdi Xu, Peide Huang, Yaru Niu, Visak Kumar, Jielin Qiu, Chao Fang, Kuan-Hui Lee, Xuewei Qi, Henry Lam, Bo Li, Ding Zhao

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Continual Reinforcement Learning with Group Symmetries.

Shiqi Liu, Mengdi Xu, Peide Huang, Yongkang Liu, Kentaro Oguchi, Ding Zhao

CoRR, 2022

Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability.

Mengdi Xu, Zuxin Liu, Peide Huang, Wenhao Ding, Zhepeng Cen, Bo Li, Ding Zhao

CoRR, 2022

Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation.

Peide Huang, Mengdi Xu, Jiacheng Zhu, Laixi Shi, Fei Fang, Ding Zhao

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Coalitional Fairness of Autonomous Vehicles at a T-Intersection.

Diana Gómez, Haohong Lin, Peide Huang, Corey Harper, Ding Zhao

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

Scalable Safety-Critical Policy Evaluation with Accelerated Rare Event Sampling.

Mengdi Xu, Peide Huang, Fengpei Li, Jiacheng Zhu, Xuewei Qi, Kentaro Oguchi, Zhiyuan Huang, Henry Lam, Ding Zhao

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Robust Reinforcement Learning as a Stackelberg Game via Adaptively-Regularized Adversarial Training.

Peide Huang, Mengdi Xu, Fei Fang, Ding Zhao

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021

Accelerated Policy Evaluation: Learning Adversarial Environments with Adaptive Importance Sampling.

Mengdi Xu, Peide Huang, Fengpei Li, Jiacheng Zhu, Xuewei Qi, Kentaro Oguchi, Zhiyuan Huang, Henry Lam, Ding Zhao

CoRR, 2021