Zobrazeno 1 - 10
of 12 670
pro vyhledávání: '"WANG, HAIYAN"'
Autor:
Wang, Haiyan, Yuan, Ye
Personal interaction data can be effectively modeled as individual graphs for each user in recommender systems.Graph Neural Networks (GNNs)-based recommendation techniques have become extremely popular since they can capture high-order collaborative
Externí odkaz:
http://arxiv.org/abs/2412.08066
Autor:
Niu, Chang, Long, Linjia, Zhang, Yizhi, Lin, Zehao, Tan, Pukun, Lin, Jian-Yu, Wu, Wenzhuo, Wang, Haiyan, Ye, Peide D.
The ongoing demand for more energy-efficient, high-performance electronics is driving the exploration of innovative materials and device architectures, where interfaces play a crucial role due to the continuous downscaling of device dimensions. Tellu
Externí odkaz:
http://arxiv.org/abs/2412.04306
Autor:
Wang, Haiyan
This paper analyzes the stationary distributions of populations governed by the discrete stochastic logistic and Ricker difference equations at equilibrium examines with the gamma distribution. We identify mathematical relationships between the intri
Externí odkaz:
http://arxiv.org/abs/2411.15859
Autor:
Wang, Haiyan
Stochastic models play an essential role in accounting for the variability and unpredictability seen in real-world. This paper focuses on the application of the gamma distribution to analysis of the stationary distributions of populations governed by
Externí odkaz:
http://arxiv.org/abs/2411.10167
Autor:
Zhou, Jie, Zhang, Qiming, Gong, Jiarui, Lu, Yi, Liu, Yang, Abbasi, Haris, Qiu, Haining, Kim, Jisoo, Lin, Wei, Kim, Donghyeok, Li, Yiran, Ng, Tien Khee, Jang, Hokyung, Liu, Dong, Wang, Haiyan, Ooi, Boon S., Ma, Zhenqiang
Semiconductor heterojunctions are foundational to many advanced electronic and optoelectronic devices. However, achieving high-quality, lattice-mismatched interfaces remains challenging, limiting both scalability and device performance. Semiconductor
Externí odkaz:
http://arxiv.org/abs/2411.09713
Dynamic dispatching rules that allocate resources to tasks in real-time play a critical role in ensuring efficient operations of many automated material handling systems across industries. Traditionally, the dispatching rules deployed are typically t
Externí odkaz:
http://arxiv.org/abs/2411.02584
In-situ Study of Understanding the Resistive Switching Mechanisms of Nitride-based Memristor Devices
Autor:
Zhang, Di, Dhall, Rohan, Schneider, Matthew M., Song, Chengyu, Dou, Hongyi, Kunwar, Sundar, Yazzie, Natanii R., Ciston, Jim, Cucciniello, Nicholas G., Roy, Pinku, Pettes, Michael T., Watt, John, Kuo, Winson, Wang, Haiyan, McCabe, Rodney J., Chen, Aiping
Interface-type resistive switching (RS) devices with lower operation current and more reliable switching repeatability exhibits great potential in the applications for data storage devices and ultra-low-energy computing. However, the working mechanis
Externí odkaz:
http://arxiv.org/abs/2410.23185
This paper proposes a multi-agent reinforcement learning (MARL) approach to learn dynamic dispatching strategies, which is crucial for optimizing throughput in material handling systems across diverse industries. To benchmark our method, we developed
Externí odkaz:
http://arxiv.org/abs/2409.18435
Autor:
Yang, Zihao, Wei, Xiucheng, Roy, Pinku, Zhang, Di, Lu, Ping, Dhole, Samyak, Wang, Haiyan, Cucciniello, Nicholas, Patibandla, Nag, Chen, Zhebo, Zeng, Hao, Jia, Quanxi, Zhu, Mingwei
Publikováno v:
Materials 2023, 16, 7468
We report a milestone in achieving large-scale, ultrathin (~5 nm) superconducting NbN thin films on 300 mm Si wafers using a high-volume manufacturing (HVM) industrial physical vapor deposition (PVD) system. The NbN thin films possess remarkable stru
Externí odkaz:
http://arxiv.org/abs/2408.05621
Electrocardiograms (ECG), which record the electrophysiological activity of the heart, have become a crucial tool for diagnosing these diseases. In recent years, the application of deep learning techniques has significantly improved the performance o
Externí odkaz:
http://arxiv.org/abs/2406.16928