no code implementations • 26 Apr 2024 • Tianbao Zhou, Zhixin Liu, Yingying Xu
The results indicate that public debt expansions are larger than their contractions in duration and amplitude, aligning with the "deficit bias hypothesis" and being more pronounced in EMs than in AEs.
1 code implementation • 19 Jul 2022 • Long Chen, Yingying Xu, Fangyi Xu, Qian Hu, Zhenzhou Tang
In addition, this work fully considers the heterogeneity of SNs (i. e. differentiated sensing range and deployment cost) and three-dimensional (3-D) deployment scenarios.
no code implementations • 23 Mar 2022 • Minghui Wu, Yangdi Xu, Yingying Xu, Guangwei Wu, Qingqing Chen, Hongxiang Lin
In this paper, we propose a stable optimization method for the forward-model-free, LVM-based DIP model for sparse-view CBCT.
no code implementations • 27 Feb 2021 • Yingying Xu, Ming Cai, Lanfen Lin, Yue Zhang, Hongjie Hu, Zhiyi Peng, Qiaowei Zhang, Qingqing Chen, Xiongwei Mao, Yutaro Iwamoto, Xian-Hua Han, Yen-Wei Chen, Ruofeng Tong
In this paper, we propose a phase attention residual network (PA-ResSeg) to model multi-phase features for accurate liver tumor segmentation, in which a phase attention (PA) is newly proposed to additionally exploit the images of arterial (ART) phase to facilitate the segmentation of portal venous (PV) phase.
no code implementations • ICCV 2021 • Huimin Huang, Lanfen Lin, Yue Zhang, Yingying Xu, Jing Zheng, Xiongwei Mao, Xiaohan Qian, Zhiyi Peng, Jianying Zhou, Yen-Wei Chen, Ruofeng Tong
Semi-supervised learning (SSL) algorithms have attracted much attentions in medical image segmentation by leveraging unlabeled data, which challenge in acquiring massive pixel-wise annotated samples.
no code implementations • 25 Dec 2019 • Alia Abbara, Yoshiyuki Kabashima, Tomoyuki Obuchi, Yingying Xu
These results are considered to be exact in the thermodynamic limit on locally tree-like networks, such as the regular random or Erd\H{o}s--R\'enyi graphs.
1 code implementation • 14 Jan 2019 • Johan Pensar, Yingying Xu, Santeri Puranen, Maiju Pesonen, Yoshiyuki Kabashima, Jukka Corander
Learning the undirected graph structure of a Markov network from data is a problem that has received a lot of attention during the last few decades.
no code implementations • 8 Nov 2017 • Ayaka Sakata, Yingying Xu
Through asymptotic analysis, we show the correspondence between the density evolution of SCAD-AMP and the replica symmetric solution.
no code implementations • 17 Sep 2014 • Angélique Drémeau, Christophe Schülke, Yingying Xu, Devavrat Shah
These are notes from the lecture of Devavrat Shah given at the autumn school "Statistical Physics, Optimization, Inference, and Message-Passing Algorithms", that took place in Les Houches, France from Monday September 30th, 2013, till Friday October 11th, 2013.