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pro vyhledávání: '"Geng, Zijie"'
Autor:
Wang, Zhihai, Geng, Zijie, Tu, Zhaojie, Wang, Jie, Qian, Yuxi, Xu, Zhexuan, Liu, Ziyan, Xu, Siyuan, Tang, Zhentao, Kai, Shixiong, Yuan, Mingxuan, Hao, Jianye, Li, Bin, Zhang, Yongdong, Wu, Feng
The increasing complexity of modern very-large-scale integration (VLSI) design highlights the significance of Electronic Design Automation (EDA) technologies. Chip placement is a critical step in the EDA workflow, which positions chip modules on the
Externí odkaz:
http://arxiv.org/abs/2407.15026
Learning neural operators for solving partial differential equations (PDEs) has attracted great attention due to its high inference efficiency. However, training such operators requires generating a substantial amount of labeled data, i.e., PDE probl
Externí odkaz:
http://arxiv.org/abs/2401.09516
Autor:
Li, Xijun, Zhu, Fangzhou, Zhen, Hui-Ling, Luo, Weilin, Lu, Meng, Huang, Yimin, Fan, Zhenan, Zhou, Zirui, Kuang, Yufei, Wang, Zhihai, Geng, Zijie, Li, Yang, Liu, Haoyang, An, Zhiwu, Yang, Muming, Li, Jianshu, Wang, Jie, Yan, Junchi, Sun, Defeng, Zhong, Tao, Zhang, Yong, Zeng, Jia, Yuan, Mingxuan, Hao, Jianye, Yao, Jun, Mao, Kun
In an era of digital ubiquity, efficient resource management and decision-making are paramount across numerous industries. To this end, we present a comprehensive study on the integration of machine learning (ML) techniques into Huawei Cloud's OptVer
Externí odkaz:
http://arxiv.org/abs/2401.05960
In the past few years, there has been an explosive surge in the use of machine learning (ML) techniques to address combinatorial optimization (CO) problems, especially mixed-integer linear programs (MILPs). Despite the achievements, the limited avail
Externí odkaz:
http://arxiv.org/abs/2310.02807
Autor:
Wang, Jie, Yang, Rui, Geng, Zijie, Shi, Zhihao, Ye, Mingxuan, Zhou, Qi, Ji, Shuiwang, Li, Bin, Zhang, Yongdong, Wu, Feng
Generalization in partially observed markov decision processes (POMDPs) is critical for successful applications of visual reinforcement learning (VRL) in real scenarios. A widely used idea is to learn task-relevant representations that encode task-re
Externí odkaz:
http://arxiv.org/abs/2302.09601
Autor:
Geng, Zijie, Xie, Shufang, Xia, Yingce, Wu, Lijun, Qin, Tao, Wang, Jie, Zhang, Yongdong, Wu, Feng, Liu, Tie-Yan
De novo molecular generation is an essential task for science discovery. Recently, fragment-based deep generative models have attracted much research attention due to their flexibility in generating novel molecules based on existing molecule fragment
Externí odkaz:
http://arxiv.org/abs/2302.01129
Generalization across different environments with the same tasks is critical for successful applications of visual reinforcement learning (RL) in real scenarios. However, visual distractions -- which are common in real scenes -- from high-dimensional
Externí odkaz:
http://arxiv.org/abs/2205.10218
Publikováno v:
In Journal of Energy Storage 1 April 2024 83
Akademický článek
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Autor:
Pi, Zheshun1,2 (AUTHOR), Liu, Weici1,3 (AUTHOR), Song, Chenghu1 (AUTHOR), Zhu, Chuandong4,5 (AUTHOR), Liu, Jiwei1 (AUTHOR), Wang, Lu6 (AUTHOR), He, Zhao1 (AUTHOR), Yang, Chengliang7,8 (AUTHOR), Wu, Lei1 (AUTHOR), Liu, Tianshuo9 (AUTHOR), Geng, Zijie10 (AUTHOR), Tebbutt, Scott J.7,8 (AUTHOR) fzhang@njmu.edu.cn, Liu, Ningning6 (AUTHOR) fzhang@njmu.edu.cn, Wan, Yuan4 (AUTHOR) liuningning@shsmu.edu.cn, Zhang, Faming2 (AUTHOR) liuningning@shsmu.edu.cn, Mao, Wenjun1,3 (AUTHOR) fzhang@njmu.edu.cn
Publikováno v:
iMeta. Sep2024, p1. 7p. 3 Illustrations.