Zobrazeno 1 - 10
of 78 777
pro vyhledávání: '"AN Yuting"'
Autor:
LI Haoping, DU Xinyi, ZHU Chengbiao, JIN Zhuhong, CHEN Xinyi, YU Botao, LI Jingrui, AN Yuting
Publikováno v:
Taiyuan Ligong Daxue xuebao, Vol 55, Iss 4, Pp 603-611 (2024)
Purposes In actual processing of factories, the varying health status of each machine can cause machine failures and subsequently affect the processing and construction time. This article focuses on the problem of flexible job shops with machine dist
Externí odkaz:
https://doaj.org/article/445916c9cd05423b85123828683294cf
We advance the theory of parametric bootstrap in constructing highly efficient empirical best (EB) prediction intervals of small area means. The coverage error of such a prediction interval is of the order $O(m^{-3/2})$, where $m$ is the number of sm
Externí odkaz:
http://arxiv.org/abs/2410.11238
Safety-critical scenarios are infrequent in natural driving environments but hold significant importance for the training and testing of autonomous driving systems. The prevailing approach involves generating safety-critical scenarios automatically i
Externí odkaz:
http://arxiv.org/abs/2410.08453
Autor:
Liu, Dancheng, Yang, Jason, Albrecht-Buehler, Ishan, Qin, Helen, Li, Sophie, Hu, Yuting, Nassereldine, Amir, Xiong, Jinjun
Speech is a fundamental aspect of human life, crucial not only for communication but also for cognitive, social, and academic development. Children with speech disorders (SD) face significant challenges that, if unaddressed, can result in lasting neg
Externí odkaz:
http://arxiv.org/abs/2410.11865
Diffusion models play a pivotal role in contemporary generative modeling, claiming state-of-the-art performance across various domains. Despite their superior sample quality, mainstream diffusion-based stochastic samplers like DDPM often require a la
Externí odkaz:
http://arxiv.org/abs/2410.04760
Autor:
Chen, Ziru, Chen, Shijie, Ning, Yuting, Zhang, Qianheng, Wang, Boshi, Yu, Botao, Li, Yifei, Liao, Zeyi, Wei, Chen, Lu, Zitong, Dey, Vishal, Xue, Mingyi, Baker, Frazier N., Burns, Benjamin, Adu-Ampratwum, Daniel, Huang, Xuhui, Ning, Xia, Gao, Song, Su, Yu, Sun, Huan
The advancements of language language models (LLMs) have piqued growing interest in developing LLM-based language agents to automate scientific discovery end-to-end, which has sparked both excitement and skepticism about the true capabilities of such
Externí odkaz:
http://arxiv.org/abs/2410.05080
Swarm robotics, or very large-scale robotics (VLSR), has many meaningful applications for complicated tasks. However, the complexity of motion control and energy costs stack up quickly as the number of robots increases. In addressing this problem, ou
Externí odkaz:
http://arxiv.org/abs/2410.02510
Non-ideal measurement computed tomography (NICT), which sacrifices optimal imaging standards for new advantages in CT imaging, is expanding the clinical application scope of CT images. However, with the reduction of imaging standards, the image quali
Externí odkaz:
http://arxiv.org/abs/2410.01591
This paper studies the robust portfolio selection problem under a state-dependent confidence set. The investor invests in a financial market with a risk-free asset and a risky asset. The ambiguity-averse investor faces uncertainty over the drift of t
Externí odkaz:
http://arxiv.org/abs/2409.19571
Autor:
Hong, Fangzhou, Guzov, Vladimir, Kim, Hyo Jin, Ye, Yuting, Newcombe, Richard, Liu, Ziwei, Ma, Lingni
As the prevalence of wearable devices, learning egocentric motions becomes essential to develop contextual AI. In this work, we present EgoLM, a versatile framework that tracks and understands egocentric motions from multi-modal inputs, e.g., egocent
Externí odkaz:
http://arxiv.org/abs/2409.18127