Zobrazeno 1 - 10
of 7 112
pro vyhledávání: '"Ye, Chen"'
Large Language Models (LLMs) have shown excellent performance in language understanding, text generation, code synthesis, and many other tasks, while they still struggle in complex multi-step reasoning problems, such as mathematical reasoning. In thi
Externí odkaz:
http://arxiv.org/abs/2406.02100
Autor:
Huang, Chang, Zhao, Junqiao, Zhu, Shatong, Zhou, Hongtu, Ye, Chen, Feng, Tiantian, Jiang, Changjun
Value function factorization methods are commonly used in cooperative multi-agent reinforcement learning, with QMIX receiving significant attention. Many QMIX-based methods introduce monotonicity constraints between the joint action value and individ
Externí odkaz:
http://arxiv.org/abs/2405.08036
Autor:
Huang, Kai, Zhao, Junqiao, Lin, Jiaye, Zhu, Zhongyang, Song, Shuangfu, Ye, Chen, Feng, Tiantian
Uncertainty in LiDAR measurements, stemming from factors such as range sensing, is crucial for LIO (LiDAR-Inertial Odometry) systems as it affects the accurate weighting in the loss function. While recent LIO systems address uncertainty related to ra
Externí odkaz:
http://arxiv.org/abs/2405.01316
Accurate and dense mapping in large-scale environments is essential for various robot applications. Recently, implicit neural signed distance fields (SDFs) have shown promising advances in this task. However, most existing approaches employ projectiv
Externí odkaz:
http://arxiv.org/abs/2401.03412
Publikováno v:
IEEE Journal of Biomedical and Health Informatics, 2024
To promote the generalization ability of breast tumor segmentation models, as well as to improve the segmentation performance for breast tumors with smaller size, low-contrast and irregular shape, we propose a progressive dual priori network (PDPNet)
Externí odkaz:
http://arxiv.org/abs/2310.13574
Autor:
Wang, Xueyan, Sun, Lin, Ye, Chen, Huang, Zhen, Han, Kun, Huang, Ke, Yang, Allen Jian, Zeng, Shengwei, Loh, Xian Jun, Zhu, Qiang, Venkatesan, T., Ariando, Ariando, Wang, X. Renshaw
Electronic correlation and reconstruction are two important factors that play a critical role in shaping the magnetic and electronic properties of correlated low-dimensional systems. Here, we report a competition between the electronic correlation an
Externí odkaz:
http://arxiv.org/abs/2310.04024
Autor:
Zhang, Hai, Yu, Hang, Zhao, Junqiao, Zhang, Di, Huang, Chang, Zhou, Hongtu, Zhang, Xiao, Ye, Chen
Designing and deriving effective model-based reinforcement learning (MBRL) algorithms with a performance improvement guarantee is challenging, mainly attributed to the high coupling between model learning and policy optimization. Many prior methods t
Externí odkaz:
http://arxiv.org/abs/2309.12671
LiDAR-based place recognition plays a crucial role in Simultaneous Localization and Mapping (SLAM) and LiDAR localization. Despite the emergence of various deep learning-based and hand-crafting-based methods, rotation-induced place recognition failur
Externí odkaz:
http://arxiv.org/abs/2308.12870
Local geometric information, i.e. normal and distribution of points, is crucial for LiDAR-based simultaneous localization and mapping (SLAM) because it provides constraints for data association, which further determines the direction of optimization
Externí odkaz:
http://arxiv.org/abs/2307.09531