Zobrazeno 1 - 10
of 42 918
pro vyhledávání: '"Zhao,Wei"'
Autor:
Li, Shisong, Ma, Yongchao, Ma, Kang, Liu, Weibo, Li, Nanjia, Liu, Xiaohu, Peng, Lisha, Zhao, Wei, Huang, Songling, Yu, Xinjie
With the adoption of the revised International System of Units (SI), the Kibble balance has become a pivotal instrument for mass calibrations against the Planck constant, $h$. One of the major focuses in the Kibble balance community is prioritizing e
Externí odkaz:
http://arxiv.org/abs/2412.12521
Publikováno v:
AAAI 2025
Mixup is a data augmentation technique that enhances model generalization by interpolating between data points using a mixing ratio $\lambda$ in the image domain. Recently, the concept of mixup has been adapted to the graph domain through node-centri
Externí odkaz:
http://arxiv.org/abs/2412.08144
Autor:
Gong, Zhefei, Ding, Pengxiang, Lyu, Shangke, Huang, Siteng, Sun, Mingyang, Zhao, Wei, Fan, Zhaoxin, Wang, Donglin
In robotic visuomotor policy learning, diffusion-based models have achieved significant success in improving the accuracy of action trajectory generation compared to traditional autoregressive models. However, they suffer from inefficiency due to mul
Externí odkaz:
http://arxiv.org/abs/2412.06782
Publikováno v:
Phys. Rev. Research 6, 043163 (2024)
Quantum mechanics empowers the emergence of quantum advantages in various fields, including quantum algorithms. Quantum PageRank is a promising tool for a future quantum internet. Recently, arbitrary phase rotations (APR) have been introduced in the
Externí odkaz:
http://arxiv.org/abs/2411.13114
This paper develops a comprehensive physics-based model (PBM) that spans a wide operational range, including varying temperatures, charge/discharge conditions, and real-world field data cycles. The PBM incorporates key factors such as hysteresis effe
Externí odkaz:
http://arxiv.org/abs/2411.12152
Low-dose CT (LDCT) significantly reduces the radiation dose received by patients, however, dose reduction introduces additional noise and artifacts. Currently, denoising methods based on convolutional neural networks (CNNs) face limitations in long-r
Externí odkaz:
http://arxiv.org/abs/2411.07930
Autor:
Liu, Yun, Li, Peng, Yan, Xuefeng, Nan, Liangliang, Wang, Bing, Chen, Honghua, Gong, Lina, Zhao, Wei, Wei, Mingqiang
The core of self-supervised point cloud learning lies in setting up appropriate pretext tasks, to construct a pre-training framework that enables the encoder to perceive 3D objects effectively. In this paper, we integrate two prevalent methods, maske
Externí odkaz:
http://arxiv.org/abs/2411.06041
Autor:
Wang, Fan, Zou, Zhilin, Sakla, Nicole, Partyka, Luke, Rawal, Nil, Singh, Gagandeep, Zhao, Wei, Ling, Haibin, Huang, Chuan, Prasanna, Prateek, Chen, Chao
Publikováno v:
Volume 99, 2025, 103373
Characterization of breast parenchyma in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a challenging task owing to the complexity of underlying tissue structures. Existing quantitative approaches, like radiomics and deep learning
Externí odkaz:
http://arxiv.org/abs/2411.03464
Visual Question-Answering, a technology that generates textual responses from an image and natural language question, has progressed significantly. Notably, it can aid in tracking and inquiring about daily activities, crucial in healthcare monitoring
Externí odkaz:
http://arxiv.org/abs/2410.20034
Recent research has focused on literary machine translation (MT) as a new challenge in MT. However, the evaluation of literary MT remains an open problem. We contribute to this ongoing discussion by introducing LITEVAL-CORPUS, a paragraph-level paral
Externí odkaz:
http://arxiv.org/abs/2410.18697