A fast and stable algorithm for downdating the singular value decomposition. - Jieyuan Zhang; Shengguo Li; Lizhi Cheng; Xiangke Liao; Guangquan Cheng (Comput. Math. Appl., 2014)

Incremental Analysis for Probabilistic Programs. - Jieyuan Zhang; Yulei Sui; Jingling Xue (SAS, 2017)

Incremental precision-preserving symbolic inference for probabilistic programs. - Jieyuan Zhang; Jingling Xue (PLDI, 2019)

Incremental Static Analysis of Probabilistic Programs. - Jieyuan Zhang (2019)

Combined Reinforcement Learning via Artificial Potential Field: A Case Study in Pommerman. - Yuqi Zhu; Shengze Li; Jieyuan Zhang; Xinhai Xu (ISCAS, 2021)

A Monitoring Method Integrating Terrestrial Laser Scanning and Unmanned Aerial Vehicles for Different Landslide Deformation Patterns. - Nan Jiang; Haibo Li; Yuxiang Hu; Jieyuan Zhang; Wei Dai; Congjiang Li; Jiawen Zhou (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021)

Diverse Effective Relationship Exploration for Cooperative Multi-Agent Reinforcement Learning. - Hao Jiang 035; Yuntao Liu 004; Shengze Li; Jieyuan Zhang; Xinhai Xu; Donghong Liu (CIKM, 2022)

A Dual-View Knowledge Enhancing Self-Attention Network for Sequential Recommendation. - Hao Tang; Feng Zhang; Xinhai Xu; Jieyuan Zhang; Donghong Liu (ICTAI, 2022)

Dynamic Agent Allocation with Reinforcement Learning for Applying Behavior Trees in Games. - Xianglong Li; Yuan Li; Xinhai Xu; Donghong Liu; Jieyuan Zhang (CogSci, 2023)

Optimizing 3D Mantle Convection Simulations on Multi-cores. - Zhicheng Zhang; Jie Liu 002; Shengguo Li; Fan Yuan; Xiaoxiong Zhu; Qinglin Wang; Jieyuan Zhang (HPCC/DSS/SmartCity/DependSys, 2023)

Temporal Task Graph Based Dynamic Agent Allocation for Applying Behavior Trees in Multi-agent Games. - Xianglong Li; Yuan Li; Jieyuan Zhang; Xinhai Xu; Donghong Liu (ICONIP (8), 2023)

Agent Allocation-Action Learning with Dynamic Heterogeneous Graph in Multi-Task Games. - Xianglong Li; Yuan Li; Jieyuan Zhang; Xinhai Xu; Donghong Liu (IEICE Trans. Inf. Syst., 2024)

Generative subgoal oriented multi-agent reinforcement learning through potential field. - Shengze Li; Hao Jiang 035; Yuntao Liu 004; Jieyuan Zhang; Xinhai Xu; Donghong Liu (Neural Networks, 2024)

Efficient 3D Recognition with Event-driven Spike Sparse Convolution. - Xuerui Qiu; Man Yao; Jieyuan Zhang; Yuhong Chou; Ning Qiao; Shibo Zhou; Bo Xu 002; Guoqi Li (AAAI, 2025)

Quantized Spike-driven Transformer. - Xuerui Qiu; Malu Zhang; Jieyuan Zhang; Wenjie Wei; Honglin Cao; Junsheng Guo; Rui-Jie Zhu 003; Yimeng Shan; Yang Yang 002; Haizhou Li 001 (ICLR, 2025)

QP-SNN: Quantized and Pruned Spiking Neural Networks. - Wenjie Wei; Malu Zhang; Zijian Zhou 005; Ammar Belatreche; Yimeng Shan; Yu Liang; Honglin Cao; Jieyuan Zhang; Yang Yang (ICLR, 2025)

QP-SNN: Quantized and Pruned Spiking Neural Networks. - Wenjie Wei; Malu Zhang; Zijian Zhou 005; Ammar Belatreche; Yimeng Shan; Yu Liang; Honglin Cao; Jieyuan Zhang; Yang Yang 002 (CoRR, 2025)

SDTrack: A Baseline for Event-based Tracking via Spiking Neural Networks. - Yimeng Shan; Zhenbang Ren; Haodi Wu; Wenjie Wei; Rui-Jie Zhu 003; Shuai Wang; Dehao Zhang; Yichen Xiao; Jieyuan Zhang; Kexin Shi; Jingzhinan Wang; Jason K. Eshraghian; et al. (CoRR, 2025)

Training-Free ANN-to-SNN Conversion for High-Performance Spiking Transformer. - Jingya Wang; Xin Deng; Wenjie Wei; Dehao Zhang; Shuai Wang; Qian Sun; Jieyuan Zhang; Hanwen Liu; Ning Xie; Malu Zhang (CoRR, 2025)