Uni6D: A Unified CNN Framework without Projection Breakdown for 6D Pose Estimation. - Xiaoke Jiang; Donghai Li; Hao Chen 103; Ye Zheng; Rui Zhao 001; Liwei Wu (CVPR, 2022)

Layer-Wisely Supervised Learning For One-Shot Neural Architecture Search. - Yifei Chen; Zhourui Guo; Qiyue Yin; Hao Chen 103; Kaiqi Huang (IJCNN, 2022)

Multi-Agent Uncertainty Sharing for Cooperative Multi-Agent Reinforcement Learning. - Hao Chen 103; Guangkai Yang; Junge Zhang; Qiyue Yin; Kaiqi Huang (IJCNN, 2022)

RACA: Relation-Aware Credit Assignment for Ad-Hoc Cooperation in Multi-Agent Deep Reinforcement Learning. - Hao Chen 103; Guangkai Yang; Junge Zhang; Qiyue Yin; Kaiqi Huang (IJCNN, 2022)

FGA-NAS: Fast Resource-Constrained Architecture Search by Greedy-ADMM Algorithm. - Yifei Chen; Junge Zhang; Qiaozhe Li; Hao Chen 103; Kaiqi Huang (IJCNN, 2022)

Consensus Learning for Cooperative Multi-Agent Reinforcement Learning. - Zhiwei Xu 005; Bin Zhang 052; Dapeng Li 001; Zeren Zhang; Guangchong Zhou; Hao Chen 103; Guoliang Fan (AAAI, 2023)

Uncertainty Quantification via Spatial-Temporal Tweedie Model for Zero-inflated and Long-tail Travel Demand Prediction. - Xinke Jiang; Dingyi Zhuang; Xianghui Zhang; Hao Chen 103; Jiayuan Luo; Xiaowei Gao (CIKM, 2023)

Explicitly Learning Policy Under Partial Observability in Multiagent Reinforcement Learning. - Chen Yang; Guangkai Yang; Hao Chen 103; Junge Zhang (IJCNN, 2023)

Underexplored Subspace Mining for Sparse-Reward Cooperative Multi-Agent Reinforcement Learning. - Yang Yu 056; Qiyue Yin; Junge Zhang; Hao Chen 103; Kaiqi Huang (IJCNN, 2023)

PDiT: Interleaving Perception and Decision-making Transformers for Deep Reinforcement Learning. - Hangyu Mao; Rui Zhao 001; Ziyue Li 002; Zhiwei Xu 005; Hao Chen 103; Yiqun Chen 004; Bin Zhang 052; Zhen Xiao; Junge Zhang; Jiangjin Yin (AAMAS, 2024)

GATE: Guided Contrastive State Space for Multi-agent Reinforcement Learning. - Hao Chen 103; Bin Zhang 052; Guoliang Fan (ICONIP (4), 2024)

SGCD: Subgroup Contribution Decomposition for Multi-Agent Reinforcement Learning. - Hao Chen 103; Bin Zhang 052; Guoliang Fan (IJCNN, 2024)

Timeseries Suppliers Allocation Risk Optimization via Deep Black Litterman Model. - Jiayuan Luo; Wentao Zhang 008; Yuchen Fang 001; Xiaowei Gao; Dingyi Zhuang; Hao Chen 103; Xinke Jiang (CoRR, 2024)

TC-RAG:Turing-Complete RAG's Case study on Medical LLM Systems. - Xinke Jiang; Yue Fang; Rihong Qiu; Haoyu Zhang; Yongxin Xu; Hao Chen 103; Wentao Zhang 008; Ruizhe Zhang 013; Yuchen Fang 001; Xu Chu; Junfeng Zhao 001; Yasha Wang (CoRR, 2024)

Time Series Supplier Allocation via Deep Black-Litterman Model. - Xinke Jiang; Wentao Zhang 008; Yuchen Fang 001; Xiaowei Gao; Hao Chen 103; Haoyu Zhang; Dingyi Zhuang; Jiayuan Luo (AAAI, 2025)

TC-RAG: Turing-Complete RAG's Case study on Medical LLM Systems. - Xinke Jiang; Yue Fang; Rihong Qiu; Haoyu Zhang; Yongxin Xu; Hao Chen 103; Wentao Zhang 008; Ruizhe Zhang 013; Yuchen Fang 001; Xinyu Ma; Xu Chu; Junfeng Zhao 001; et al. (ACL (1), 2025)

Exploration via Embracing Diversity in Reinforcement Learning for Sparse-Reward Procedurally-Generated Tasks. - Pei Xu; Hao Chen 103; Wenjie Yang 005; Kaiqi Huang (IEEE Trans. Syst. Man Cybern. Syst., 2025)