Zobrazeno 1 - 10
of 1 480
pro vyhledávání: '"SUN Yuxin"'
Autor:
Zhao, Tong, Zhong, Shulin, Sun, Yuxin, Wu, Defan, Zhang, Chunyi, Shi, Rui, Chen, Hao, Ni, Zhenyi, Pi, Xiaodong, Ma, Xiangyang, Lu, Yunhao, Yang, Deren
Pressure-induced phase transformation occurs during silicon (Si) wafering processes. \b{eta}-tin (Si-II) phase is formed at high pressures, followed by the transformation to Si-XII, Si-III or/and amorphous Si ({\alpha}-Si) phases during the subsequen
Externí odkaz:
http://arxiv.org/abs/2412.04732
Autor:
Wu, Yueh-Chun, Halász, Gábor B., Damron, Joshua T., Gai, Zheng, Zhao, Huan, Sun, Yuxin, Dahmen, Karin A, Sohn, Changhee, Carlson, Erica W., Hua, Chengyun, Lin, Shan, Song, Jeongkeun, Lee, Ho Nyung, Lawrie, Benjamin J.
Thermally driven transitions between ferromagnetic and paramagnetic phases are characterized by critical behavior with divergent susceptibilities, long-range correlations, and spin dynamics that can span kHz to GHz scales as the material approaches t
Externí odkaz:
http://arxiv.org/abs/2410.19158
We study the complexity of Non-Gaussian Component Analysis (NGCA) in the Statistical Query (SQ) model. Prior work developed a general methodology to prove SQ lower bounds for this task that have been applicable to a wide range of contexts. In particu
Externí odkaz:
http://arxiv.org/abs/2403.04744
We study the problem of learning mixtures of linear classifiers under Gaussian covariates. Given sample access to a mixture of $r$ distributions on $\mathbb{R}^n$ of the form $(\mathbf{x},y_{\ell})$, $\ell\in [r]$, where $\mathbf{x}\sim\mathcal{N}(0,
Externí odkaz:
http://arxiv.org/abs/2310.11876
Publikováno v:
Xiehe Yixue Zazhi, Vol 15, Iss 6, Pp 1456-1462 (2024)
Skeletal maturity can reflect an individual's developmental status and predict their future growth potential, provide clinicians with valuable diagnostic information. In recent years, significant progress has been made in imaging techniques for asses
Externí odkaz:
https://doaj.org/article/79b1facbbba84665b6041df6da24fa26
We present new insights and a novel paradigm (StEik) for learning implicit neural representations (INR) of shapes. In particular, we shed light on the popular eikonal loss used for imposing a signed distance function constraint in INR. We show analyt
Externí odkaz:
http://arxiv.org/abs/2305.18414
Publikováno v:
Journal of Chemical Physics; 11/14/2024, Vol. 161 Issue 18, p1-7, 7p
Autor:
Sun, Yuxin1 (AUTHOR), Liu, Mingjian2 (AUTHOR), Bai, Baochao2 (AUTHOR), Liu, Yichao2 (AUTHOR), Sheng, Panjie2 (AUTHOR), An, Jiangbo2 (AUTHOR), Bao, Ruiying1 (AUTHOR), Liu, Tingyu1 (AUTHOR) 18604752777@163.com, Shi, Kai1 (AUTHOR) nmshikai@126.com
Publikováno v:
Scientific Reports. 10/24/2024, Vol. 14 Issue 1, p1-18. 18p.
Autor:
Sun, Yuxin1,2 (AUTHOR) yuxinsun@bupt.edu.cn, Liu, Wenjun1,2 (AUTHOR) jungliu@bupt.edu.cn, Tian, Ye1,2 (AUTHOR) ye.tian@bupt.edu.cn
Publikováno v:
Mathematics (2227-7390). Oct2024, Vol. 12 Issue 19, p2985. 16p.
We study the problem of PAC learning a single neuron in the presence of Massart noise. Specifically, for a known activation function $f: \mathbb{R} \to \mathbb{R}$, the learner is given access to labeled examples $(\mathbf{x}, y) \in \mathbb{R}^d \ti
Externí odkaz:
http://arxiv.org/abs/2210.09949