Peide Huang

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 23

Top Topics

Latent Variables

Bayesian Nonparametric

Reinforcement Learning

Top Venues

BuildSys@SenSys

Publications

Gaocai Fu, Yu Jiang, Jun Xiao, Peide Huang, Xu Luo, Minhui Ni, Xianjv Liu
Construction of Virtual Simulation Teaching Platform for Risk Experimental Projects in VR Environment. ICSIM (2024)
Yihang Yao, Zuxin Liu, Zhepeng Cen, Peide Huang, Tingnan Zhang, Wenhao Yu, Ding Zhao
Gradient shaping for multi-constraint safe reinforcement learning. L4DC (2024)
Peide Huang, Wenhao Ding, Jonathan Francis, Bingqing Chen, Ding Zhao
CaDRE: Controllable and Diverse Generation of Safety-Critical Driving Scenarios using Real-World Trajectories. CoRR (2024)
Yiwen Dong, Yuyan Wu, Jesse R. Codling, Jatin Aggarwal, Peide Huang, Wenhao Ding, Hugo Latapie, Pei Zhang, Hae Young Noh
GameVibes: Vibration-based Crowd Monitoring for Sports Games through Audience-Game-Facility Association Modeling. BuildSys@SenSys (2023)
Jielin Qiu, Jiacheng Zhu, Mengdi Xu, Peide Huang, Michael A. Rosenberg, Douglas Weber, Emerson Liu, Ding Zhao
Cardiac Disease Diagnosis on Imbalanced Electrocardiography Data Through Optimal Transport Augmentation. ICASSP (2023)
Yiwen Dong, Peide Huang, Hae Young Noh
Characterizing Crowd Preferences on Stadium Facilities through Dynamic Inverse Reinforcement Learning. BuildSys@SenSys (2023)
Peide Huang, Xilun Zhang, Ziang Cao, Shiqi Liu, Mengdi Xu, Wenhao Ding, Jonathan Francis, Bingqing Chen, Ding Zhao
What Went Wrong? Closing the Sim-to-Real Gap via Differentiable Causal Discovery. CoRR (2023)
Shiqi Liu, Mengdi Xu, Peide Huang, Xilun Zhang, Yongkang Liu, Kentaro Oguchi, Ding Zhao
Continual Vision-based Reinforcement Learning with Group Symmetries. CoRL (2023)
Yihang Yao, Zuxin Liu, Zhepeng Cen, Peide Huang, Tingnan Zhang, Wenhao Yu, Ding Zhao
Gradient Shaping for Multi-Constraint Safe Reinforcement Learning. CoRR (2023)
Mengdi Xu, Peide Huang, Yaru Niu, Visak Kumar, Jielin Qiu, Chao Fang, Kuan-Hui Lee, Xuewei Qi, Henry Lam, Bo Li, Ding Zhao
Group Distributionally Robust Reinforcement Learning with Hierarchical Latent Variables. AISTATS (2023)
Peide Huang, Xilun Zhang, Ziang Cao, Shiqi Liu, Mengdi Xu, Wenhao Ding, Jonathan Francis, Bingqing Chen, Ding Zhao
What Went Wrong? Closing the Sim-to-Real Gap via Differentiable Causal Discovery. CoRL (2023)
Mengdi Xu, Peide Huang, Wenhao Yu, Shiqi Liu, Xilun Zhang, Yaru Niu, Tingnan Zhang, Fei Xia, Jie Tan, Ding Zhao
Creative Robot Tool Use with Large Language Models. CoRR (2023)
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
Multimodal Representation Learning of Cardiovascular Magnetic Resonance Imaging. CoRR (2023)
Mengdi Xu, Peide Huang, Fengpei Li, Jiacheng Zhu, Xuewei Qi, Kentaro Oguchi, Zhiyuan Huang, Henry Lam, Ding Zhao
Scalable Safety-Critical Policy Evaluation with Accelerated Rare Event Sampling. IROS (2022)
Shiqi Liu, Mengdi Xu, Peide Huang, Yongkang Liu, Kentaro Oguchi, Ding Zhao
Continual Reinforcement Learning with Group Symmetries. CoRR (2022)
Peide Huang, Mengdi Xu, Fei Fang, Ding Zhao
Robust Reinforcement Learning as a Stackelberg Game via Adaptively-Regularized Adversarial Training. IJCAI (2022)
Mengdi Xu, Peide Huang, Yaru Niu, Visak Kumar, Jielin Qiu, Chao Fang, Kuan-Hui Lee, Xuewei Qi, Henry Lam, Bo Li, Ding Zhao
Group Distributionally Robust Reinforcement Learning with Hierarchical Latent Variables. CoRR (2022)
Peide Huang, Mengdi Xu, Jiacheng Zhu, Laixi Shi, Fei Fang, Ding Zhao
Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation. NeurIPS (2022)
Diana Gómez, Haohong Lin, Peide Huang, Corey Harper, Ding Zhao
Coalitional Fairness of Autonomous Vehicles at a T-Intersection. ITSC (2022)
Peide Huang, Mengdi Xu, Jiacheng Zhu, Laixi Shi, Fei Fang, Ding Zhao
Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation. CoRR (2022)
Mengdi Xu, Zuxin Liu, Peide Huang, Wenhao Ding, Zhepeng Cen, Bo Li, Ding Zhao
Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability. CoRR (2022)
Peide Huang, Mengdi Xu, Fei Fang, Ding Zhao
Robust Reinforcement Learning as a Stackelberg Game via Adaptively-Regularized Adversarial Training. CoRR (2022)
Mengdi Xu, Peide Huang, Fengpei Li, Jiacheng Zhu, Xuewei Qi, Kentaro Oguchi, Zhiyuan Huang, Henry Lam, Ding Zhao
Accelerated Policy Evaluation: Learning Adversarial Environments with Adaptive Importance Sampling. CoRR (2021)