Simulating Noisy Quantum Circuits with Matrix Product Density Operators. - Song Cheng; Chenfeng Cao; Chao Zhang; Yongxiang Liu; Shi-Yao Hou; Pengxiang Xu; Bei Zeng (CoRR, 2020)

Robust Facial Manipulation Detection via Domain Generalization. - Pengxiang Xu; Xue Mei; Yi Wei; Tiancheng Qian (ICCAI, 2021)

DST: Data Selection and joint Training for Learning with Noisy Labels. - Yi Wei; Xue Mei; Xin Liu; Pengxiang Xu (CoRR, 2021)

NG+ : A Multi-Step Matrix-Product Natural Gradient Method for Deep Learning. - Minghan Yang; Dong Xu; Qiwen Cui; Zaiwen Wen; Pengxiang Xu (CoRR, 2021)

Filtration network: A frame sampling strategy via deep reinforcement learning for video captioning. - Tiancheng Qian; Xue Mei; Pengxiang Xu; Kangqi Ge; Zhelei Qiu (J. Intell. Fuzzy Syst., 2021)

Simulating noisy variational quantum eigensolver with local noise models. - Jinfeng Zeng; Zipeng Wu; Chenfeng Cao; Chao Zhang; Shi-Yao Hou; Pengxiang Xu; Bei Zeng (Quantum Eng., 2021)

Data fusing and joint training for learning with noisy labels. - Yi Wei; Mei Xue; Xin Liu; Pengxiang Xu (Frontiers Comput. Sci., 2022)

Sketch-Based Empirical Natural Gradient Methods for Deep Learning. - Minghan Yang; Dong Xu; Zaiwen Wen; Mengyun Chen; Pengxiang Xu (J. Sci. Comput., 2022)

An Efficient Fisher Matrix Approximation Method for Large-Scale Neural Network Optimization. - Minghan Yang; Dong Xu; Qiwen Cui; Zaiwen Wen; Pengxiang Xu (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Improving GPU Energy Efficiency through an Application-transparent Frequency Scaling Policy with Performance Assurance. - Yijia Zhang; Qiang Wang; Zhe Lin; Pengxiang Xu; Bingqiang Wang (EuroSys, 2024)

Unlocking High Performance with Low-Bit NPUs and CPUs for Highly Optimized HPL-MxP on Cloud Brain II. - Weicheng Xue; Kai Yang; Yongxiang Liu; Dengdong Fan; Pengxiang Xu; Yonghong Tian 001 (SC, 2024)

Block Coordinate Descent Methods for Optimization under J-Orthogonality Constraints with Applications. - Di He; Ganzhao Yuan; Xiao Wang; Pengxiang Xu (CoRR, 2024)

Uncertainty guided test-time training for face forgery detection. - Pengxiang Xu; Yang He; Jian Yang; Shanshan Zhang (Comput. Vis. Image Underst., 2024)

Detecting facial manipulated images via one-class domain generalization. - Pengxiang Xu; Zhiyuan Ma 003; Xue Mei; Jie Shen (Multim. Syst., 2024)

SGEMM-cube: Emulating FP32 GEMM on Ascend NPUs Using FP16 Cube Units with Precision Recovery. - Weicheng Xue; Baisong Xu; Kai Yang; Yongxiang Liu; Dengdeng Fan; Pengxiang Xu; Yonghong Tian 001 (CoRR, 2025)