Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Siderophore-producing bacteria reduce soil cadmium bioavailability and alleviate cadmium stress in alfalfa.

Ecotoxicology and environmental safety·2026
Same author

Statistics and AI - A Fireside Conversation.

Harvard data science review·2026
Same author

An Ultrastable Hydrogen-Bonded Organic Framework With Two-Dimensional Pores for Rapid Adsorption Kinetics and Efficient Xe/Kr Separation.

Angewandte Chemie (International ed. in English)·2026
Same author

Fresh-seawater interface shapes nitrogen fate in a subtropical estuary: Insights from multi-isotopic and metagenomic analyses.

Water research·2026
Same author

Sn-Mediated Amorphous NiFeP Electroless Plating on Nickel Mesh for Stable High-Current Oxygen Evolution Reaction.

ACS applied materials & interfaces·2026
Same author

Integrating multi-stage interventions for harmful algal blooms effective management.

Journal of environmental management·2026
Same journal

Instrumental Variable Estimation of Marginal Structural Mean Models for Time-Varying Treatment.

Journal of the American Statistical Association·2026
Same journal

Semiparametric Joint Modeling for Survival Analysis with Longitudinal Covariates.

Journal of the American Statistical Association·2026
Same journal

Dimension Reduction for Large-Scale Federated Data: Statistical Rate and Asymptotic Inference.

Journal of the American Statistical Association·2026
Same journal

Facilitating Heterogeneous Effect Estimation via Statistically Efficient Categorical Modifiers.

Journal of the American Statistical Association·2026
Same journal

Nonparametric Density Estimation of a Long-Term Trend from Repeated Semicontinuous Data.

Journal of the American Statistical Association·2026
Same journal

Functional Integrative Bayesian Analysis of High-dimensional Multiplatform Clinicogenomic Data.

Journal of the American Statistical Association·2026
查看所有相关文章

相关实验视频

Updated: Jun 10, 2025

Generating Strictly Controlled Stimuli for Figure Recognition Experiments
05:39

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

Published on: March 18, 2019

5.2K

通过结构,监督和生成对抗学习来测试指向的环形图.

Chengchun Shi1, Yunzhe Zhou2, Lexin Li2

  • 1London School of Economics and Political Science.

Journal of the American Statistical Association
|October 17, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种针对定向非循环图 (DAG) 的新假设测试方法. 新方法容纳非线性关联和时间依赖的数据,增强复杂网络中的因果推理.

关键词:
大脑连接网络的大脑连接网络.定向非循环图是指向非循环图.生成性的对抗性网络.假设测试 测试 假设测试多层感知神经网络多层感知神经网络

更多相关视频

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids
08:21

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

2.6K
Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
14:06

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

46.4K

相关实验视频

Last Updated: Jun 10, 2025

Generating Strictly Controlled Stimuli for Figure Recognition Experiments
05:39

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

Published on: March 18, 2019

5.2K
Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids
08:21

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

2.6K
Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
14:06

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

46.4K

科学领域:

  • 统计 统计 统计 统计
  • 机器学习 机器学习
  • 计算神经科学是一种神经科学.

背景情况:

  • 定向非循环图 (DAG) 对于表示因果关系至关重要.
  • 现有的DAG推理方法通常假定线性模型和独立数据,限制了它们的适用性.
  • 需要灵活的假设测试方法来处理复杂的数据结构.

研究的目的:

  • 为定向非循环图 (DAG) 提出一种新的假设测试方法.
  • 开发一种能够容纳非线性关联和时间依赖数据的测试.
  • 为DAG推理提供一个统计严格的框架.

主要方法:

  • 利用灵活的神经网络学习者进行假设测试.
  • 开发了一种允许随机变量之间非线性关联的方法.
  • 对于具有不同受试者数量或时间点的测试,建立了不对称的保证.

主要成果:

  • 通过模拟证明了拟议的假设测试方法的有效性.
  • 成功地应用了测试来分析大脑连接网络.
  • 该方法在复杂的,时间依赖的系统中推断因果结构方面表现有前途.

结论:

  • 拟议的方法提供了一个强大的新工具,用于在指向非循环图中测试假设.
  • 它通过处理非线性和时间依赖数据来克服现有方法的局限性.
  • 这种方法对包括神经科学在内的各种科学领域的因果推理具有广泛的影响.