Zobrazeno 1 - 10
of 9 920
pro vyhledávání: '"Lin, Jie"'
Autor:
Xu, Kaixin, Wang, Zhe, Chen, Chunyun, Geng, Xue, Lin, Jie, Yang, Xulei, Wu, Min, Li, Xiaoli, Lin, Weisi
Vision transformers have emerged as a promising alternative to convolutional neural networks for various image analysis tasks, offering comparable or superior performance. However, one significant drawback of ViTs is their resource-intensive nature,
Externí odkaz:
http://arxiv.org/abs/2407.02068
Exploring proper way to conduct multi-speech feature fusion for cross-corpus speech emotion recognition is crucial as different speech features could provide complementary cues reflecting human emotion status. While most previous approaches only extr
Externí odkaz:
http://arxiv.org/abs/2406.07437
Timbre, the sound's unique "color", is fundamental to how we perceive and appreciate music. This review explores the multifaceted world of timbre perception and representation. It begins by tracing the word's origin, offering an intuitive grasp of th
Externí odkaz:
http://arxiv.org/abs/2405.13661
Autor:
Liu, Cheng, Wang, Xiaofeng, Zhang, Xiaobing, Kovalev, Mikhail, Lin, Jie, Xi, Gaobo, Mo, Jun, Li, Gaici, Peng, Haowei, Li, Xin, Xia, Qiqi, Iskandar, Abdusamatjan, Zeng, Xiangyun, Wang, Letian, Zhu, Liying, Song, Xuan, Guo, Jincheng, Jiang, Xiaojun, Yan, Shengyu, Zhang, Jicheng
We present a comprehensive photometric and spectroscopic analysis of the short-period ($\sim$5.32 hours) and low-mass eclipsing binary TMTSJ0803 discovered by Tsinghua-Ma Huateng Telescope for Survey (TMTS). By fitting the light curves and radial vel
Externí odkaz:
http://arxiv.org/abs/2405.10595
Autor:
Geng, Xue, Wang, Zhe, Chen, Chunyun, Xu, Qing, Xu, Kaixin, Jin, Chao, Gupta, Manas, Yang, Xulei, Chen, Zhenghua, Aly, Mohamed M. Sabry, Lin, Jie, Wu, Min, Li, Xiaoli
Deep neural networks (DNNs) have been widely used in many artificial intelligence (AI) tasks. However, deploying them brings significant challenges due to the huge cost of memory, energy, and computation. To address these challenges, researchers have
Externí odkaz:
http://arxiv.org/abs/2405.06038
Autor:
Feng, Fabo, Rui, Yicheng, Du, Zhimao, Lin, Qing, Zhang, Congcong, Zhou, Dan, Cui, Kaiming, Ogihara, Masahiro, Yang, Ming, Lin, Jie, Cai, Yongzhi, Yang, Taozhi, Pang, Xiaoying, Jian, Mingjie, Li, Wenxiong, Guo, Hengxiao, Shi, Xian, Shi, Jianchun, Li, Jianyang, Guo, Kangrou, Yao, Song, Chen, Aming, Jia, Peng, Tan, Xianyu, Jenkins, James S., Jiang, Hongxuan, Zhang, Mingyuan, Li, Kexin, Xiao, Guangyao, Zheng, Shuyue, Xuan, Yifan, Zheng, Jie, He, Min, Jones, Hugh R. A., Song, Cuiying
Giant planets like Jupiter and Saturn, play important roles in the formation and habitability of Earth-like planets. The detection of solar system analogs that have multiple cold giant planets is essential for our understanding of planet habitability
Externí odkaz:
http://arxiv.org/abs/2404.07149
Federated learning (FL) involves multiple heterogeneous clients collaboratively training a global model via iterative local updates and model fusion. The generalization of FL's global model has a large gap compared with centralized training, which is
Externí odkaz:
http://arxiv.org/abs/2402.18949
The Luria-Delbr\"uck model is a classic model of population dynamics with random mutations, that has been used historically to prove that random mutations drive evolution. In typical scenarios, the relevant mutation rate is exceedingly small, and mut
Externí odkaz:
http://arxiv.org/abs/2402.13339
Autor:
Yan, Zhen, Yu, Wenfei, Page, Kim L., Lin, Jie, Li, Di, Niu, Chenhui, Law, Casey, Zhang, Bing, Chatterjee, Shami, Zhang, Xian, Anna-Thomas, Reshma
Fast radio bursts (FRBs) are bright, millisecond-duration radio bursts of cosmic origin. There have been several dozen FRBs found to repeat. Among them, those precisely localized provide the best opportunity to probe their multi-wavelength counterpar
Externí odkaz:
http://arxiv.org/abs/2402.12084
Autor:
Lin, Jie, MacLellan, Benjamin, Ghanbari, Sobhan, Belleville, Julie, Tran, Khuong, Robichaud, Luc, Melko, Roger G., Lo, Hoi-Kwong, Roztocki, Piotr
GraphiQ is a versatile open-source framework for designing photonic graph state generation schemes, with a particular emphasis on photon-emitter hybrid circuits. Built in Python, GraphiQ consists of a suite of design tools, including multiple simulat
Externí odkaz:
http://arxiv.org/abs/2402.09285