Zobrazeno 1 - 10
of 5 203
pro vyhledávání: '"Xie, Min"'
Graph neural network (GNN) models play a pivotal role in numerous tasks involving graph-related data analysis. Despite their efficacy, similar to other deep learning models, GNNs are susceptible to adversarial attacks. Even minor perturbations in gra
Externí odkaz:
http://arxiv.org/abs/2406.03833
We introduce a novel meta-analysis framework to combine dependent tests under a general setting, and utilize it to synthesize various microbiome association tests that are calculated from the same dataset. Our development builds upon the classical me
Externí odkaz:
http://arxiv.org/abs/2404.09353
This paper presents a novel method to make statistical inferences for both the model support and regression coefficients in a high-dimensional logistic regression model. Our method is based on the repro samples framework, in which we conduct statisti
Externí odkaz:
http://arxiv.org/abs/2403.09984
Vibrational resonance (VR) is a nonlinear phenomenon in which the system response to a weak signal can be resonantly enhanced by applying a high-frequency modulation signal with an appropriate amplitude. The majority of VR research has focused on amp
Externí odkaz:
http://arxiv.org/abs/2402.18852
Prognostics and health management (PHM) is essential for industrial operation and maintenance, focusing on predicting, diagnosing, and managing the health status of industrial systems. The emergence of the ChatGPT-Like large-scale language model (LLM
Externí odkaz:
http://arxiv.org/abs/2312.14945
Publikováno v:
Chapter 2 from Gi-Joon Nam and Jason Cong, Modern Circuit Placement Best Practices and Results, 2007, Springer, reproduced with permission of Springer Science+Business Media, LLC
The mixed-size placement benchmarks described in this book chapter directly address several of the shortcomings in previously published suboptimality benchmarks. Two new sets of placement examples are constructed, one targeting the role of nonlocal n
Externí odkaz:
http://arxiv.org/abs/2305.16413
Publikováno v:
Zhejiang dianli, Vol 43, Iss 4, Pp 121-128 (2024)
Convolutional neural networks (CNNs) struggle to efficiently capture contextual information of power equipment such as arresters and GIS inlet casings due to their limited receptive fields, thereby affecting detection performance. To address th
Externí odkaz:
https://doaj.org/article/7631d8aac43e4c82946b90f62424d782
Autor:
Hu Xuanyi, Xie Min, Liu Siyi, Wu Yulu, Wu Xiangrui, Liu Yuanyuan, He Changjiu, Dai Guangzhi, Wang Qiang
Publikováno v:
Sichuan jingshen weisheng, Vol 37, Iss 1, Pp 39-45 (2024)
BackgroundThe occurrence rate of dangerous behaviors in patients with severe mental disorders is higher than that of the general population. In China, there is limited research on the prediction of dangerous behaviors in community-dwelling patients
Externí odkaz:
https://doaj.org/article/fb4424bb58df4e98b61f1df68bb42615
In this paper, we present a new and effective simulation-based approach to conduct both finite- and large-sample inference for high-dimensional linear regression models. This approach is developed under the so-called repro samples framework, in which
Externí odkaz:
http://arxiv.org/abs/2209.09299
A class of nonparametric two-sample tests has been proposed in this article. As a generalization of the original \v{S}id\'aks' test, the proposed test statistic is developed as the sum of the maximal precedence and maximal exceedance statistics. Unli
Externí odkaz:
http://arxiv.org/abs/2208.02521