Zobrazeno 1 - 10
of 1 193
pro vyhledávání: '"Zhang, Xiaoran"'
Autor:
Wang, Chengbo, Zhang, Xiaoran
In this manuscript, we focus on the more delicate nonlinearity of the semilinear wave equation $$\partial_{t}^2 u-\Delta_{\mathbb{R}^3}u=|u|^{p_S}\mu(|u|)\ ,u(0,x)=\varepsilon u_0,\ u_t(0,x)=\varepsilon u_1\ ,$$ where $p_S=1+\sqrt{2}$ is the Strauss
Externí odkaz:
http://arxiv.org/abs/2405.12761
Autor:
Zhang, Xiaoran, Stendahl, John C., Staib, Lawrence, Sinusas, Albert J., Wong, Alex, Duncan, James S.
We propose an adaptive training scheme for unsupervised medical image registration. Existing methods rely on image reconstruction as the primary supervision signal. However, nuisance variables (e.g. noise and covisibility) often cause the loss of cor
Externí odkaz:
http://arxiv.org/abs/2312.00837
Autor:
Zhang, Xiaoran, Pak, Daniel H., Ahn, Shawn S., Li, Xiaoxiao, You, Chenyu, Staib, Lawrence, Sinusas, Albert J., Wong, Alex, Duncan, James S.
This paper proposes a heteroscedastic uncertainty estimation framework for unsupervised medical image registration. Existing methods rely on objectives (e.g. mean-squared error) that assume a uniform noise level across the image, disregarding the het
Externí odkaz:
http://arxiv.org/abs/2312.00836
Autor:
Zhang, Xiaoran
In this paper, we verified the critical conjecture in our previous work \cite{wang2023wave} on two-dimensional hyperbolic space, that is, concerning nonlinear wave equations with logarithmic nonlinearity, which behaves like $\left(\ln {1}/{|u|}\right
Externí odkaz:
http://arxiv.org/abs/2309.10384
Autor:
Wang, Chengbo, Zhang, Xiaoran
In light of the exponential decay of solutions of linear wave equations on hyperbolic spaces $\mathbb{H}^n$, to illustrate the critical nature, we investigate nonlinear wave equations with logarithmic nonlinearity, which behaves like $\left(\ln {1}/{
Externí odkaz:
http://arxiv.org/abs/2304.01595
Autor:
Xing, Xiangzhuo, Wang, Chao, Yu, Linchao, Xu, Jie, Zhang, Chutong, Zhang, Mengge, Huang, Song, Zhang, Xiaoran, Yang, Bingchao, Chen, Xin, Zhang, Yongsheng, Guo, Jian-gang, Shi, Zhixiang, Ma, Yanming, Chen, Changfeng, Liu, Xiaobing
Publikováno v:
Nat. Commun. 14, 5991 (2023)
The recent report of near-ambient superconductivity in nitrogen doped lutetium hydride has triggered a worldwide fanaticism and raised major questions about the latest claims. An intriguing phenomenon of color changes in pressurized samples from blue
Externí odkaz:
http://arxiv.org/abs/2303.17587
Autor:
You, Chenyu, Dai, Weicheng, Liu, Fenglin, Min, Yifei, Su, Haoran, Zhang, Xiaoran, Li, Xiaoxiao, Clifton, David A., Staib, Lawrence, Duncan, James S.
Recent studies on contrastive learning have achieved remarkable performance solely by leveraging few labels in the context of medical image segmentation. Existing methods mainly focus on instance discrimination and invariant mapping. However, they fa
Externí odkaz:
http://arxiv.org/abs/2209.13476
Learning spatial-temporal correspondences in cardiac motion from images is important for understanding the underlying dynamics of cardiac anatomical structures. Many methods explicitly impose smoothness constraints such as the $\mathcal{L}_2$ norm on
Externí odkaz:
http://arxiv.org/abs/2209.00726
Publikováno v:
Computers & Structures, Volume 285, September 2023, 107071
A single-step high-order implicit time integration scheme with controllable numerical dissipation at high frequencies is presented for the transient analysis of structural dynamic problems. The amount of numerical dissipation is controlled by a user-
Externí odkaz:
http://arxiv.org/abs/2206.04183
Autor:
You, Chenyu, Xiang, Jinlin, Su, Kun, Zhang, Xiaoran, Dong, Siyuan, Onofrey, John, Staib, Lawrence, Duncan, James S.
Many medical datasets have recently been created for medical image segmentation tasks, and it is natural to question whether we can use them to sequentially train a single model that (1) performs better on all these datasets, and (2) generalizes well
Externí odkaz:
http://arxiv.org/abs/2206.01369